Ever since presenting on C++ AMP at the AMD Fusion conference in June, then the Gamefest conference in August, and the BUILD conference in September, I've had numerous requests about my material from folks that want to re-deliver the same session. The C++ AMP session I put together has evolved over the 3 presentations to its final form that I used at BUILD, so that is the one I recommend you base yours on.
Please get the slides and the recording from channel9 (I'll refer to slide numbers below).
(slide 3, 04:18-08:18) Start with a demo, on my dual-GPU machine. I've been using the N-Body sample.
(slide 4) Use an nvidia slide that has additional examples of performance improvements that customers enjoy with heterogeneous computing.
(slide 5) Talk a bit about the differences today between CPU and GPU hardware, leading to the fact that these will continue to co-exist and that GPUs are great for data parallel algorithms, but not much else today. One is a jack of all trades and the other is a number cruncher.
(slide 6) Use the APU example from amd, as one indication that the hardware space is still in motion, emphasizing that the C++ AMP solution is a data parallel API, not a GPU API. It has a future proof design for hardware we have yet to see.
(slide 7) Provide more meta-data, as blogged about when I first introduced C++ AMP.
(slide 9-11) Introduce C++ AMP coding with a simplistic array-addition algorithm – the slides speak for themselves.
(Slide 14-16) array, array_view and comparison between them.
(slide 22) bring it altogether with a matrix multiplication example.
(slide 23-24) accelerator, and accelerator_view.
(slide 26-29) Introduce tiling incl. tiled matrix multiplication [tiling probably deserves a whole session instead of 6 minutes!].
(slide 34,37) Briefly touch on the concurrency visualizer. It supports GPU profiling, but enhancements specific to C++ AMP come at the Beta timeframe.
(slide 35-36, 51:54-59:16) Demonstrate the GPU debugging experience in VS 11.
(slide 39) Re-iterate some of the points of slide 7, and add the point that C++ AMP is an open specification.
(slide 40) Links to content – see slide – including where all your questions should go: http://social.msdn.microsoft.com/Forums/en/parallelcppnative/threads.
The BUILD recording and slides are valid for the VS 11 Beta and beyond, with regards to C++ AMP - so watch the session and download those slides. Additionally, if you are going to repeat the session, I have updated the slides including some tweaks and you can download the updated deck here (note the slide numbers above do not map exactly to the new deck).
"But I don't have time for a full blown session, I only need 2 (or just 1, or 3) C++ AMP slides to use in my session on related topic X"
If all you want is a small number of slides, you can take some from the session above and customize them. But because I am so nice, I have created some slides for you, including talking points in the notes section. Download them here.
One of the FAQs we receive is whether C++ AMP can be used to target the CPU.
For targeting multi-core we have a technology we released with VS2010 called PPL, which has had enhancements for VS 11 – that is what you should be using! FYI, it also has a Linux implementation via Intel's TBB which conforms to the same interface.
When you choose to use C++ AMP, you choose to take advantage of massively parallel hardware, through accelerators like the GPU.
Having said that, you can always use the accelerator class to check if you are running on a system where the is no hardware with a DirectX 11 driver, and decide what alternative code path you wish to follow.
In fact, if you do nothing in code, if the runtime does not find DX11 hardware to run your code on, it will choose the WARP accelerator which will run your code on the CPU, taking advantage of multi-core and SSE2 (depending on the CPU capabilities WARP also uses SSE3 and SSE 4.1 – it does not currently use AVX and on such systems you hopefully have a DX 11 GPU anyway).
It is our fallback CPU solution, not intended as a primary target of C++ AMP.
WARP stands for Windows Advanced Rasterization Platform and you can read old info on this MSDN page on WARP.
What is new in Windows 8 Developer Preview is that WARP now supports DirectCompute, which is what C++ AMP builds on.
It is not currently clear if we will have a CPU fallback solution for non-Windows 8 platforms when we ship.
When you create a WARP accelerator, its is_emulated property returns true.
WARP does not currently support double precision.
BTW, when we refer to WARP, we refer to this accelerator described above. If we use lower case "warp", that refers to a bunch of threads that run concurrently in lock step and share the same instruction. In the VS 11 Developer Preview, the size of warp in our Ref emulator is 4 – Ref is another emulator that runs on the CPU, but it is extremely slow not intended for production, just for debugging.
We ended the previous post with a mechanical transformation of the C++ AMP matrix multiplication example to the tiled model and in the process introduced tiled_index and tiled_extent. This is part 2.
You all know that in regular CPU code, static variables have the same value regardless of which thread accesses the static variable. This is in contrast with non-static local variables, where each thread has its own copy.
Back to C++ AMP, the same rules apply and each thread has its own value for local variables in your lambda, whereas all threads see the same global memory, which is the data they have access to via the array and array_view.
Note that tile_static variables are scoped and have the lifetime of the tile, and they cannot have constructors or destructors.
In amp.h one of the types introduced is tile_barrier. You cannot construct this object yourself (although if you had one, you could use a copy constructor to create another one). So how do you get one of these? You get it, from a tiled_index object. Beyond the 4 properties returning index objects, tiled_index has another property, barrier, that returns a tile_barrier object. The tile_barrier class exposes the method wait (and other wait overloads).
…in the code above, all threads in the tile will reach line 16 before a single one progresses to line 17. Note that all threads must be able to reach the barrier, i.e. if you had branchy code in such a way which meant that there is a chance that not all threads could reach line 16, then the code above would be illegal.
So now that we added to our understanding the concepts of tile_static and tile_barrier, let me obfuscate rewrite the matrix multiplication code so that it takes advantage of tile_static memory. Before you start reading this, I suggest you get a cup of your favorite non-alcoholic beverage to enjoy while you try to fully understand the code.
Notice that all the code up to line 9 is the same as per the changes we made in part 1 of tiling introduction. If you squint, the body of the lambda itself preserves the original algorithm on lines 10, 11, and 17, 18, and 21. The difference being that those lines use new indexing and the tile_static arrays; the tile_static arrays are declared and initialized on the brand new lines 13-15. On those lines we copy from the global memory represented by the array_view objects (a and b), to the tile_static vanilla arrays (locA and locB) – we are copying enough to fit a tile. Because in the code that follows on line 18 we expect the data for this tile to be in the tile_static storage, we need to synchronize the threads within each tile with a barrier, which we do on line 16 (to avoid accessing uninitialized memory on line 18). We also need to synchronize the threads within a tile on line 19, again to avoid the race between lines 14, 15 (retrieving the next set of data for each tile and overwriting the previous set) and line 18 (not being done processing the previous set of data). Luckily, as part of the awesome C++ AMP debugger in Visual Studio there is an option that helps you find such races, but that is a story for another blog post another time.
May I suggest reading the next section, and then coming back to re-read and walk through this code with pen and paper to really grok what is going on, if you haven't already? Cool.
Why would I introduce this tiling complexity into my code?
Funny you should ask that, I was just about to tell you. There is only one reason we tiled our extent, had to deal with finding a good tile size, ensure the number of threads we schedule are correctly divisible with the tile size, had to use a tiled_index instead of a normal index, and had to understand tile_barrier and to figure out where we need to use it, and double the size of our lambda in terms of lines of code: the reason is to be able to use tile_static memory.
Why do we want to use tile_static memory? Because accessing tile_static memory is around 10 times faster than accessing the global memory on an accelerator like the GPU, e.g. in the code above, if you can get 150GB/second accessing data from the array_view a, you can get 1500GB/second accessing the tile_static array locA. And since by definition you are dealing with really large data sets, the savings really pay off. We have seen tiled implementations being twice as fast as their non-tiled counterparts.
Now, some algorithms will not have performance benefits from tiling (and in fact may deteriorate), e.g. algorithms that require you to go only once to global memory may not benefit from tiling, since with tiling you already have to fetch the data once from global memory! Other algorithms may benefit, but you may decide that you are happy with your code being 50 times faster than the serial-version you had, and you do not need to invest to make it 100 times faster. Also algorithms with more than 3 dimensions, which C++ AMP supports in the simple model, cannot be tiled.
Also note that in future releases, we may invest in making the non-tiled model, which already uses tiling under the covers, go the extra step and use tile_static memory on your behalf, but it is obviously way to early to commit to anything like that, and we certainly don't do any of that today.
This post assumes you are totally comfortable with, what some of us call, the simple model of C++ AMP, i.e. you could write your own matrix multiplication. We are now ready to explore the tiled model, which builds on top of the non-tiled one.
We know that when we pass an extent to the parallel_for_each call, it determines the number of threads to schedule and their index values (including dimensionality). For the single-, two-, and three- dimensional cases you can go a step further and subdivide the threads into what we call tiles of threads (others may call them thread groups).
…on the 2nd line we subdivided the single-dimensional space into 5 single-dimensional tiles each having 4 elements, and we captured that result in a concurrency::tiled_extent (a new class in amp.h).
So we start on the left with a 2-dimensional extent which has 8*6=48 threads. We then have two different examples of tiling. In the first case, in the middle, we subdivide the 48 threads into tiles where each has 4*3=12 threads, hence we have 2*2=4 tiles. In the second example, on the right, we subdivide the original input into tiles where each has 2*2=4 threads, hence we have 4*3=12 tiles. Notice how you can play with the tile size and achieve different number of tiles. The numbers you pick must be such that the original total number of threads (in our example 48), remains the same, and every tile must have the same size.
Of course, you still have no clue why you would do that, but stick with me. First, we should see how we can use this tiled_extent, since the parallel_for_each function that we know expects a extent.
It turns out that we have additional overloads of parallel_for_each that accept a tiled_extent instead of a extent. However, those overloads, also expect that the lambda you pass in accepts a concurrency::tiled_index (new in amp.h), not an index<N>. So how is a tiled_index different to an index?
Given the code above and the picture on the right, what are the values of each of the 4 index objects that the t_idx variables exposes, when the lambda is executed by T (highlighted in the picture on the right)?
Don't move on until you are comfortable with this… the picture really helps, so use it.
To turn this into a tiled example, first we need to decide our tile size. Let's say we want each tile to be 16*16 (which assumes that we'll have at least 256 threads to process, and that c.extent.size() is divisible by 256, and moreover that c.extent and c.extent are divisible by 16). So we insert at line 03 the tile size (which must be a compile time constant).
...and now this code just works and it is tiled!
The process we followed just shows the mechanical transformation that can take place from the simple model to the tiled model (think of this as step 1). In fact, when we wrote the matrix multiplication example originally, the compiler was doing this mechanical transformation under the covers for us (and it has additional smarts to deal with the cases where the total number of threads scheduled is not divisible by the tile size). The point is that the thread scheduling is always tiled, even when you use the non-explicitly-tiled model.
But with this mechanical transformation, we haven't gained anything… Hint: our goal with explicitly using the tiled model is to gain even more performance.
As part of our API tour of C++ AMP, we looked recently at parallel_for_each. I ended that post by saying we would revisit parallel_for_each after introducing array and array_view. Now is the time, so this is part 2 of parallel_for_each, and also a post that brings together everything we've seen until now.
First a visual comparison, just for fun: The beginning and end is the same, i.e. lines 0,1,12 are identical to lines 13,14,26. The double nested loop (lines 2,3,4,5 and 10,11) has been transformed into a parallel_for_each call (18,19,20 and 25). The core algorithm (lines 6,7,8,9) is essentially the same (lines 21,22,23,24). We have extra lines in the C++ AMP version (15,16,17). Now let's dig in deeper.
When we decided to convert this function to run on an accelerator, we knew we couldn't use the std::vector objects in the restrict(amp) function. So we had a choice of copying the data to the the concurrency::array<T,N> object, or wrapping the vector container (and hence its data) with a concurrency::array_view<T,N> object from amp.h – here we used the latter (lines 15,16,17). Now we can access the same data through the array_view objects (a and b) instead of the vector objects (vA and vB), and the added benefit is that we can capture the array_view objects in the lambda (lines 19-25) that we pass to the parallel_for_each call (line 18) and the data will get copied on demand for us to the accelerator.
In other words, we could have explicitly created the extent object instead of letting the array_view create it for us under the covers through the constructor overload we chose. The benefit of the extent object in this instance is that we can express that the data is indeed two dimensional, i.e a matrix. When we were using a vector object we could not do that, and instead we had to track via additional unrelated variables the dimensions of the matrix (i.e. with the integers M and W) – aren't you loving C++ AMP already?
Note that the const before the float when creating a and b, will result in the underling data only being copied to the accelerator and not be copied back – a nice optimization. A similar thing is happening on line 17 when creating array_view c, where we have indicated that we do not need to copy the data to the accelerator, through the discard_data call.
On line 18 we make the call to the C++ AMP entry point (parallel_for_each) to invoke our parallel loop or, as some may say, dispatch our kernel.
The first argument we need to pass describes how many threads we want for this computation. For this algorithm we decided that we want exactly the same number of threads as the number of elements in the output matrix, i.e. in array_view c which will eventually update the vector vC. So each thread will compute exactly one result. Since the elements in c are organized in a 2-dimensional manner we can organize our threads in a two-dimensional manner too. We don't have to think too much about how to create the first argument (a extent) since the array_view object helpfully exposes that as a property. Note that instead of c.extent we could have written extent<2>(M, N) – the result is the same in that we have specified M*N threads to execute our lambda.
The second argument is a restrict(amp) lambda that accepts an index object. Since we elected to use a two-dimensional extent as the first argument of parallel_for_each, the index will also be two-dimensional and as covered in the previous posts it represents the thread ID, which in our case maps perfectly to the index of each element in the resulting array_view.
The lambda body (lines 20-24), or as some may say, the kernel, is the code that will actually execute on the accelerator. It will be called by M*N threads and we can use those threads to index into the two input array_views (a,b) and write results into the output array_view ( c ).
The four lines (21-24) are essentially identical to the four lines of the serial algorithm (6-9). The only difference is how we index into a,b,c versus how we index into vA,vB,vC. The code we wrote with C++ AMP is much nicer in its indexing, because the dimensionality is a first class concept, so you don't have to do funny arithmetic calculating the index of where the next row starts, which you have to do when working with vectors directly (since they store all the data in a flat manner).
...and the rest of your code remains the same… how simple is that?
This is a very long post, but it also covers what are probably the classes (well, array_view at least) that you will use the most with C++ AMP, so I hope you enjoy it!
The concurrency::array and concurrency::array_view template classes represent multi-dimensional data of type T, of N dimensions, specified at compile time (and you can later access the number of dimensions via the rank property). If N is not specified, it is assumed that it is 1 (i.e. single-dimensional case). They are rectangular (not jagged).
The difference between them is that array is a container of data, whereas array_view is a wrapper of a container of data. So in that respect, array behaves like an STL container, whereas the closest thing an array_view behaves like is an STL iterator (albeit with random access and allowing you to view more than one element at a time!).
The data in the array (whether provided at creation time or added later) resides on an accelerator (which is specified at creation time either explicitly by the developer, or set to the default accelerator at creation time by the runtime) and is laid out contiguously in memory. The data provided to the array_view is not stored by/in the array_view, because the array_view is simply a view over the real source (which can reside on the CPU or other accelerator). The underlying data is copied on demand to wherever the array_view is accessed. Elements which differ by one in the least significant dimension of the array_view are adjacent in memory.
array objects must be captured by reference into the lambda you pass to the parallel_for_each call, whereas array_view objects must be captured by value (into the lambda you pass to the parallel_for_each call). After you are done reading this post, feel free to visit another post dedicated to capturing data.
You can create array_view objects from other array_view objects of the same rank and element type (shallow copy, also possible via assignment operator) so they point to the same underlying data, and you can also create array_view objects over array objects of the same rank and element type e.g.
Note: Unlike the constructors above which can be called anywhere, the ones in the rest of this section can only be called from CPU code.
You can create array objects from other array objects of the same rank and element type (copy and move constructors) and from other array_view objects, e.g.
To create an array from scratch, you need to at least specify an extent object, e.g. array<int,3> a(myExtent);. Note that instead of an explicit extent object, there are convenience overloads when N<=3 so you can specify 1-, 2-, 3- integers (dependent on the array's rank) and thus have the extent created for you under the covers. At any point, you can access the array's extent thought the extent property. The exact same thing applies to array_view (extent as constructor parameters, incl. convenience overloads, and property).
While passing only an extent object to create an array is enough (it means that the array will be written to later), it is not enough for the array_view case which must always wrap over some other container (on which it relies for storage space and actual content). So in addition to the extent object (that describes the shape you'd like to be viewing/accessing that data through), to create an array_view from another container (e.g. std::vector) you must pass in the container itself (which must expose .data() and a .size() methods, e.g. like std::array does), e.g.
Similarly, you can create an array_view from a raw pointer of data plus an extent object.
Back to the array case, to optionally initialize the array with data, you can pass an iterator pointing to the start (and optionally one pointing to the end of the source container) e.g.
We saw that arrays are bound to an accelerator at creation time, so in case you don't want the C++ AMP runtime to assign the array to the default accelerator, all array constructors have overloads that let you pass an accelerator_view object, which you can later access via the accelerator_view property.
Note that in the previous section on constructors, unlike the array case, there was no overload that accepted an accelerator_view for array_view. That is because the array_view is simply a wrapper, so the allocation of the data has already taken place before you created the array_view. When you capture an array_view variable in your call to parallel_for_each, the copy of data between the non-CPU accelerator and the CPU takes place on demand (i.e. it is implicit, versus the explicit copy that has to happen with the array). There are some subtleties to the on-demand-copying that we cover next.
Conversely, if you make a change to the underlying data through the original source (e.g. the pointer), the array_view will not "know" about those changes, unless you call its refresh method.
Finally, note that if you create an array_view of const T, then the data is copied to the accelerator on demand, but it does not get copied back, e.g.
There is also a similar mechanism to achieve the reverse, i.e. not to copy the data of an array_view to the GPU.
Both array and array_view expose two copy_to overloads that allow copying them to another array, or to another array_view, and these operations can also be achieved with assignment (via the = operator overloads).
Also both array and array_view expose a data method, to get a raw pointer to the underlying data of the array or array_view, e.g. float* f = myArr.data();. Note that for array_view, this only works when the rank is equal to 1, due to the data only being contiguous in one dimension as covered in the overview section.
Finally, there are a bunch of global concurrency::copy functions returning void (and corresponding concurrency::copy_async functions returning a future) that allow copying between arrays and array_views and iterators etc.
Note that for array, all copying described throughout this post is deep copying, as per other STL container expectations. You can never have two arrays point to the same data.
Reading or writing data elements of an array is only legal when the code executes on the same accelerator as where the array was bound to. In the array_view case, you can read/write on any accelerator, not just the one where the original data resides, and the data gets copied for you on demand. In both cases, the way you read and write individual elements is via indexing as described next.
To access (or set the value of) an element, you can index into it by passing it an index object via the subscript operator. Furthermore, if the rank is 3 or less, you can use the function ( ) operator to pass integer values instead of having to use an index object. e.g.
//and the reverse for assigning, e.g.
Note that for both array and array_view, regardless of rank, you can also pass a single integer to the subscript operator which results in a projection of the data, and (for both array and array_view) you get back an array_view of rank N-1 (or if the rank was 1, you get back just the element at that location).
In this already very long post, I am not going to cover three very cool methods (and related overloads) that both array and array_view expose: view_as, section, reinterpret_as. We'll revisit those at some point in the future, probably on the team blog.
This posts assumes that you've read my other C++ AMP posts on index<N> and extent<N>, as well as about the restrict modifier. It also assumes you are familiar with C++ lambdas (if not, follow my links to C++ documentation).
The parallel_for_each will execute the body of the lambda (which must have the restrict modifier), on the GPU. We also call the lambda body the "kernel". The kernel will be executed multiple times, once per scheduled GPU thread. The only difference in each execution is the value of the index object (aka as the GPU thread ID in this context) that gets passed to your kernel code. The number of GPU threads (and the values of each index) is determined by the extent object you pass, as described next.
So what the above means is that the lambda body with the algorithm that you wrote will get executed 6 times and the index<2> object you receive each time will have one of the values just listed above (of course, each one will only appear once, the order is indeterminate, and they are likely to call your code at the same exact time). Obviously, in real GPU programming, you'd typically be scheduling thousands if not millions of threads, not just 6.
If you've been following along you should be thinking: "that is all fine and makes sense, but what can I do in the kernel since I passed nothing else meaningful to it, and it is not returning any values out to me?"
It is a good question, and in data parallel algorithms indeed you typically want to pass some data in, perform some operation, and then typically return some results out. The way you pass data into the kernel, is by capturing variables in the lambda (again, if you are not familiar with them, follow the links about C++ lambdas), and the way you use data after the kernel is done executing is simply by using those same variables.
In the example above, the lambda was written in a fairly useless way with an empty capture list: [ ](index<2> idx) restrict(amp), where the empty square brackets means that no variables were captured.
If instead I write it like this [&](index<2> idx) restrict(amp), then all variables in the some_code_A region are made available to the lambda by reference, but as soon as I try to use any of those variables in the lambda, I will receive a compiler error. This has to do with one of the amp restrictions, where essentially only one type can be captured by reference: objects of the new concurrency::array class that I'll introduce in the next post (suffice for now to think of it as a container of data).
If I write the lambda line like this [=](index<2> idx) restrict(amp), all variables in the some_code_A region are made available to the lambda by value. This works for some types (e.g. an integer), but not for all, as per the restrictions for amp. In particular, no useful data classes work except for one new type we introduce with C++ AMP: objects of the new concurrency::array_view class, that I'll also introduce in the next post. Also note that if you capture some variable by value, you could use it as input to your algorithm, but you wouldn't be able to observe changes to it after the parallel_for_each call (e.g. in some_code_B region since it was passed by value) – the exception to this rule is the array_view since (as we'll see in a future post) it is a wrapper for data, not a container.
Finally, for completeness, you can write your lambda, e.g. like this [av, &ar](index<2> idx) restrict(amp) where av is a variable of type array_view and ar is a variable of type array - the point being you can be very specific about what variables you capture and how.
Please note that the parallel_for_each executes as if synchronous to the calling code, but in reality, it is asynchronous. I.e. once the parallel_for_each call is made and the kernel has been passed to the runtime, the some_code_B region continues to execute immediately by the CPU thread, while in parallel the kernel is executed by the GPU threads. However, if you try to access the (array or array_view) data that you captured in the lambda in the some_code_B region, your code will block until the results become available. Hence the correct statement: the parallel_for_each is as-if synchronous in terms of visible side-effects, but asynchronous in reality.
That's all for now, we'll revisit the parallel_for_each description, once we introduce properly array and array_view – coming next.
We saw in a previous post how index<N> represents a point in N-dimensional space and in this post we'll see how to define the N-dimensional space itself.
With C++ AMP, an N-dimensional space can be specified with the template class extent<N> where you define the size of each dimension.
From a look and feel perspective, you'd expect the programmatic interface of a point type and size type to be similar (even though the concepts are different). Indeed, exactly like index<N>, extent<N> is essentially a coordinate vector of N integers ordered from most- to least- significant, BUT each integer represents the size for that dimension (and hence cannot be negative).
There is the rank field returning the value of N you passed as the template parameter.
You can construct one extent from another (via the copy constructor or the assignment operator), you can construct it by passing an integer array, or via convenience constructor overloads for 1- 2- and 3- dimension extents. Note that the parameterless constructor creates an extent of the specified rank with all bounds initialized to 0.
You can access the components of the extent through the subscript operator (passing it an integer).
You can perform some arithmetic operations between extent objects through operator overloading, i.e. ==, !=, +=, -=, +, -.
There are operator overloads so that you can perform operations between an extent and an integer: -- (pre- and post- decrement), ++ (pre- and post- increment), %=, *=, /=, +=, –= and, finally, there are additional overloads for plus and minus (+,-) between extent<N> and index<N> objects, returning a new extent object as the result.
In addition to the usual suspects, extent offers a contains function that tests if an index is within the bounds of the extent (assuming an origin of zero). It also has a size function that returns the total linear size of this extent<N> in units of elements.
The extent class on its own simply defines the size of the N-dimensional space. We'll see in future posts that when you create containers (arrays) and wrappers (array_views) for your data, it is an extent<N> object that you'll need to use to create those (and use an index<N> object to index into them). We'll also see that it is a extent<N> object that you pass to the new parallel_for_each function that I'll cover in the next post.
C++ AMP introduces a new template class index, where N can be any value greater than zero, that represents a unique point in N-dimensional space, e.g. if N=2 then an index<2> object represents a point in 2-dimensional space. This class is essentially a coordinate vector of N integers representing a position in space relative to the origin of that space. It is ordered from most-significant to least-significant (so, if the 2-dimensional space is rows and columns, the first component represents the rows). The underlying type is a signed 32-bit integer, and component values can be negative.
The rank field returns N.
The default parameterless constructor returns an index with each dimension set to zero, e.g.
An index can also be created from another index through the copy constructor or assignment, e.g.
Note that there are convenience constructors (that don't require an array argument) for creating index objects of rank 1, 2, and 3, since those are the most common dimensions used, e.g.
You can access each component using the familiar subscript operator, e.g.
Once you have your multi-dimensional point represented in the index, you can now treat it as a single entity, including performing common operations between it and an integer (through operator overloading): -- (pre- and post- decrement), ++ (pre- and post- increment), %=, *=, /=, +=, -=,%, *, /, +, -. There are also operator overloads for operations between index objects, i.e. ==, !=, +=, -=, +, –.
In the next post we'll go beyond being able to represent an N-dimensional point in space, and we'll see how to define the N-dimensional space itself through the extent<N> class.
We saw previously that accelerator represents a target for our C++ AMP computation or memory allocation and that there is a notion of a default accelerator. We ended that post by introducing how one can obtain accelerator_view objects from an accelerator object through the accelerator class's default_view property and the create_view method.
The accelerator_view objects can be thought of as handles to an accelerator.
You can also construct an accelerator_view given another accelerator_view (through the copy constructor or the assignment operator overload). Speaking of operator overloading, you can also compare (for equality and inequality) two accelerator_view objects between them to determine if they refer to the same underlying accelerator.
We'll see later that when we use concurrency::array objects, the allocation of data takes place on an accelerator at array construction time, so there is a constructor overload that accepts an accelerator_view object. We'll also see later that a new concurrency::parallel_for_each function overload can take an accelerator_view object, so it knows on what target to execute the computation (represented by a lambda that the parallel_for_each also accepts).
Beyond normal usage, accelerator_view is a quality of service concept that offers isolation to multiple "consumers" of an accelerator. If in your code you are accessing the accelerator from multiple threads (or, in general, from different parts of your app), then you'll want to create separate accelerator_view objects for each thread.
When you create an accelerator_view via the create_view method of the accelerator, you pass in an option of queuing_mode_immediate or queuing_mode_automatic, which are the two members of the queuing_mode enum. At any point you can access this value from the queuing_mode property of the accelerator_view.
When the queuing_mode value is queuing_mode_automatic (which is the default), any commands sent to the device such as kernel invocations and data transfers (e.g. parallel_for_each and copy, as we'll see in future posts), will get submitted as soon as the runtime sees fit (that is the definition of immediate).
When the value of queuing_mode is queuing_mode_immediate, the commands will be submitted/flushed immediately.
To send all buffered commands to the device for execution, there is a non-blocking flush method that you can call. If you wish to block until all the commands have been sent, there is a wait method you can call (which also flushes). You can read more to understand C++ AMP's queuing_mode.
Just like accelerator, accelerator_view exposes the is_debug and version properties. In fact, you can always access the accelerator object from the accelerator property on the accelerator_view class to access the accelerator interface we looked at previously.
Accelerator also exposes a function that helps you stay aware of the progress of execution. You can read more about accelerator_view::create_marker.
If your app that uses C++ AMP to compute data also uses DirectX rendering shaders, e.g. pixel shaders, you can benefit by integrating C++ AMP into your graphics pipeline. One of the building blocks for that is being able to use the same device context from both the compute kernel and the other shaders. You can do that by going from accelerator_view to device context (and vice versa), through part of our interop API in amp.h: *get_device, create_accelerator_view. You can read more on DirectX interop.
UPDATE: I encourage you to visit a newer and better post with a C++ AMP matrix multiplication example.
Below is the before C++ AMP and after C++ AMP code. For more on what it all means, watch the recording of my C++ AMP introduction (the example below is part of the session).
At AMD's Fusion conference Herb Sutter announced in his keynote session a technology that our team has been working on that we call C++ Accelerated Massive Parallelism (C++ AMP) and during the keynote I showed a brief demo of an app built with our technology. After the keynote, I go deeper into the technology in my breakout session. If you read both those abstracts, you'll get some information about what C++ AMP is, without being too explicit since we published the abstracts before the technology was announced.
You can find the official online announcement at Soma's blog post.
is designed not only to help you address today's massively parallel hardware (i.e. GPUs and APUs), but it also future proofs your code investments with a forward looking design.
is part of Visual C++. You don't need to use a different compiler or learn different syntax.
is integrated and supported fully in Visual Studio 11. Editing, building, debugging, profiling and all the other goodness of Visual Studio work well with C++ AMP.
introduces only one core C++ language extension.
builds on DirectX (and DirectCompute in particular) which offers a great hardware abstraction layer that is ubiquitous and reliable. The architecture is such, that this point can be thought of as an implementation detail that does not surface to the API layer.
Previously I shared resources to get you started with DirectCompute, for taking advantage of GPGPUs in an a way that doesn't tie you to a hardware vendor (e.g. nvidia, amd).
I just stumbled upon and had to share a lecture series on channel9 on DirectCompute!
TIP: To subscribe to channel9 GPU content, use this RSS feed.
You know that I work on the parallel debugger in Visual Studio and I've talked about GPGPU before and I have also mentioned UX. Below is a request from my UX colleagues that pulls all of it together.
If you write and debug parallel code that uses GPUs for non-graphical, computationally intensive operations keep reading. The Microsoft Visual Studio Parallel Computing team is seeking developers for a 90-minute research study. The study will take place via LiveMeeting or at a usability lab in Redmond, depending on your preference.
The walkthrough utilizes a "paper" version of our current design. After the walkthrough, we would then show you some additional design ideas and seek your input on various design tradeoffs.
Are you interested or know someone who might be a good fit? Let us know at this address: devur@microsoft.com. Those who participate (and those who referred them), will receive a gratuity item from a list of current Microsoft products.


When you buy a bond, you might find that there is a sinking fund provision. So what is a sinking fund? This is an interesting measure that allows an entity to establish a fund for the purpose of ensuring that there is a way to repay the principal when it comes due.
The idea behind a sinking fund is to help the bond issuer to be able to more affordably retire its debt.
Normally, the sinking fund is established as a way to build up a certain degree of capital so that debt is easier to repay. The entity issuing the bond establishes the fund, and then uses money to purchase the outstanding bonds on the open market. So, instead of waiting to repay the principal when the bond reaches maturity, the issuer re-purchases the bond on the market. Now the original issuer is the bond holder, so the debt is actually retired.
Another way to use a sinking fund to repurchase debt is to make use of callable bonds. These are bonds that have provisions indicating that the issuer can recall the bond at a particular time, and for a particular price. Before you invest in a bond, make sure that you double-check the terms of the bond for information on whether or not it's callable in relation to the sinking fund. If it is, it means that you might be required to sell it back at a discount, meaning that you won't receive as much interest.
For the bond issuer (often a corporation), the sinking fund can help reduce costs and help reduce debt. The bond issue is designed to help raise capital, but it's possible that inflows improve, and the issuer is able to repay the debt earlier. The sinking fund can make this possible. The money in a sinking fund is used to buy bonds on the open market, purchasing them back as part of the regular business of the bond market.
It's also possible for issuers that think that they will be able to repay the debt sooner to establish the fund and issue callable bonds, or bonds with sinking fund provisions. That way, they have the right to repurchase bonds at a discount and retire their debt sooner.
There are also some benefits for investors. An investor can choose to purchase bonds with sinking funds in order to limit risk. A bond issuer with a sinking fund is more likely to repay all of its principal. If you are concerned about default, purchasing bonds with sinking fund options can help you avoid these problems.
The main downside to buying a bond with a sinking fund provision is that you could lose some of your expected returns. You reduce the risk of losing your principal, but you might have to put up with interest rate losses as the bond issuer is allowed to buy back the bonds at a discount.
Carefully consider your options before you make a decision about whether or not to purchase a bond with a sinking fund option. You need to make sure that you understand the risks as well as the rewards.
Nice explanation of what a sinking fund is. Not sure I fully understood it before.


text:
This PUP Alerts You of a Zombie Invasion
Posted: August 28, 2015 by Jovi Umawing
Apps are constantly created to address certain needs. The more helpful an app claims to be, especially in times of crisis, the more users would likely take interest in them. Some alert apps, however, need a much closer look.
Author's Note: We at Malwarebytes continue to do our part in educating our product users and constant blog readers about day-to-day online threats and how they can avoid falling prey to them. "PUP Friday", our latest attempt at getting users acquainted with files they may need to watch out for in the Wild Web, offers an in-depth look at some interesting and quite notable potentially unwanted programs (PUPs). Expect to see this type of content pushed out twice a month at the end of a work week.
Today, we're going to look at a potentially unwanted program (PUP) that anyone awaiting a zombie apocalypse would probably like to have: a reliable alert system. Thanks to Zombie Alert App, this is no longer a dream but a reality.
Maybe not.
The above screen is what Chrome, Firefox, and Safari users will see once they visit zombiealertapp[DOT]com, the download site of Zombie Alert. Normally, the red screen is seen when one visits malicious pages, such as pages hosting a phish or malware. But due to Google Safe Browsing, an effort that has now extended to targeting sites hosting what they call unwanted software (UwS), users can now see the same red screen if they access domains where one can download PUPs. You can read more about Google's more visible protection on their blog.
Anyway, let's dive in to see what this site and the app it serves are all about. Below is a full screenshot of the domain:
Below is a screenshot of the app's installer file (enlarged view) and its properties:
Malwarebytes Anti-Malware (MBAM) detects this file as PUP.Optional.ZombieSearch.A. Once executed, it acts like any installer would: displaying multiple graphical user interfaces (GUIs) that progresses to a successful installation, as you can see from the slideshow below:
After installation, it then executes the default system browser to open a page stating that the installation is a success.
In addition, a green pop-up box at the upper-right corner of the browser will appear, very similar to what we've seen from Coupon Alert. The box, in this case, is showing a "Zombie Level", which seems to be a risk level indicator for a "zombie threat" that is ranked from Low to High.
Clicking this pop-up box will reveal a news feed. We noticed that majority of articles on it display decidedly nonliving-impaired headlines containing the words "zombie" or "dead" (screenshot below is enlarged).
We wondered if the Zombie Alert pop-up box automatically appears on certain sites the same way as the Coupon Alert pop-up did. To test this, we visited sites with the word "zombie" (yes, even articles about Rob Zombie) in it to see if the pop-up will show by itself, but this didn't happen. In fact, the only way we could get it to appear at all was by using the assigned key combination—CTRL + ALT + Z—to open it up.
According to HerdProtect, the company behind Zombie Alert is "a primary distributor of adware type software." It's also known for other programs like TubeDimmer, Websteroids, and Secure Web. The Zombie Alert app can be found on various third-party sites that are hosting or redirecting users to free software. Below is a screenshot of one of these sites:
Pieter Arntz, a fellow analyst who also pushes posts for PUP Friday, told me that Zombie Alert reminded him of the Zombie News app, which he'd deconstructed and written about more than a year ago.
If you or someone you know own a computer affected by the Zombie Alert, please point or refer them to this forum page for its manual solution. This post also contains technical details on the program, such as the changes made it has done to a system upon installation.
There is not much apps out there that cater to users who look forward to an actual zombie invasion, which may or may not happen in the future; however, Zombie Alert isn't the kind of app one may need to survive such a brain-draining catastrophe. It may be fun to have at first because….zomg zombies! At the end of the day, all you really have is a feed that pushes out news about silly topics you may not really be interested in reading about.
Other reference(s):
MalwareTips Removal Guide for "Zombie Alert virus"
New Online Ebola Alert Tool is Anything But
Jovi Umawing
Chrome extensions that lie about their permissions
August 13, 2020 - Users have learned to review the list of permissions Chrome extensions require before installing them from the webstore. But what's the use if they lie to you?
Adware and PUPs families add push notifications as an attack vector
June 13, 2019 - Push notifications are being added to the arsenal of PUPs, adware, and even a Trojan browser extension that spams Facebook groups.
Knowing when it's worth the risk: riskware explained
May 23, 2019 - Riskware is a type of software that, while considered legitimate, can still put users at risk in some way. Learn why anti-malware vendors detect it, and how to tell whether the apps you use are riskware or not.
Privacy | Security world
How to tighten security and increase privacy on your browser
October 31, 2018 - Is your browser secure and private enough by design or do you need to worry about security, privacy, fingerprinting, ads, and cookies yourself?
Mac | Threat analysis
Mac App Store apps are stealing user data
September 7, 2018 - There are several apps in the Mac App Store that are collecting data about users that they should not be collecting. Here's what you need to know.
Senior Content Writer
Knows a bit about everything and a lot about several somethings. Writes about those somethings, usually in long-form.

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: Octopus not sending reads to slave I have the following configuration for a slave:
octopus:
  replicated: true
  fully_replicated: true
  environments:
    - staging
    # - production

  staging:
    shards:
      slave1:
        host: database_ip
        username: <%= ENV['DATABASE_USERNAME'] %>
        password: <%= ENV['DATABASE_PASSWORD'] %>
        database: <%= ENV['DATABASE_NAME'] %>

I checked pg_stat_activity from this slave and there is nothing, not a single query is running except from mine.
Am I missing something from octopus configuration? I went through the wiki but couldn't find anything else than shards.yml

A: You can try (without shards key):
octopus:
  replicated: true
  fully_replicated: true
  environments:
    - staging
    # - production

  staging:
    slave1:
      host: database_ip
      username: <%= ENV['DATABASE_USERNAME'] %>
      password: <%= ENV['DATABASE_PASSWORD'] %>
      database: <%= ENV['DATABASE_NAME'] %>

From Config file wiki

redpajama_set_name: RedPajamaStackExchange


I [fortunately?] have a few friends who have enough social influence to enable them to drag me out to events I have no desire of attending. This usually involves countless excuses on my part, then having said excuses shot down too efficiently and a half-joking ultimatum that not going would entail the end of our friendship. And this always involves rearranging my whole entire weekend schedule to make up for lost time.
So while I might actually wake up the next day, mascara smeared all over my eyelids, and concede that I was glad that I went out, that's not to say that the rest of the weekend won't be stressful. Going out actually makes me scramble out of bed at some absurd hour the next morning, and race to some secluded, quiet spot with my books for the rest of the weekend. I like to save myself the resulting panic and just putz away at whatever I have to do over the entire weekend, including Friday night.
One main reason that while friends in NYC were planning their first ever NYC Velo Cyclocross Season Kick-off event, I resolutely reasoned to myself that I could not possibly go. I wanted to. Desperately, in fact. But Federal Income Taxation of Corporate Enterprise stared up at me accusingly. It sucked. I just couldn't.
And then I woke up on Saturday in NYC and walked over bright and early to a bike shop milling about with friends and customers, and lucky for everyone in attendance, the Wafels & Dinges truck was there as well.
Inside, shots of espresso were being pulled and 'cross bikes examined. Questions were fielded and directed to a number of seasoned 'cross racers. Cards were exchanged in between bites of bacon-filled wafels. Embrocation and creams tested while talk of how the season went bounced amongst the attendees.
Maybe it was the sugar, but squeezing between new and old 'cross racers alike, there was nothing inaccessibly serious about the whole thing. Well, that's not quite accurate. The only thing really serious about the Kickoff party was the deadpan conviction that practically simmered in those who have discovered the wonders of 'cross that this was the single, most teeth-gnashing fun that you could ever have on a bicycle.
Which would sound slightly creepy if it wasn't for the fact that nearly every single person who races 'cross seems to passionately believe in this. And though cyclists tend to fall on the insane side of psychotic, there's always something to be said for consistency.
The NYC Velo Cyclocross Season Kickoff Party only served to heighten the excitement that seems to be bursting out of those in love with 'cross, just as the season starts to get into gear. And it's infectious, too. Because everyone seems to be talking about cyclocross this year.
If I had the funds and the bike, even I'd be up for embarrassing myself by face-planting in some mud on a cold, autumn New England day. And I'm pretty sure it won't just be for the wafels.


text:
Automartirio è un film muto italiano del 1917 diretto da Ivo Illuminati.

Collegamenti esterni

Film drammatici
Film diretti da Ivo Illuminati

redpajama_set_name: RedPajamaWikipedia


text:
You are here: Home > Tri-County Economy > Central Coast > Current Article
Dubroff: Litigation, criminal probe could put squeeze on oil pipeline operator
By Henry Dubroff / Friday, July 3rd, 2015 / Comments Off on Dubroff: Litigation, criminal probe could put squeeze on oil pipeline operator
Workers clean up the Refugio oil spill.
When Barry Cappello litigates, people listen.
Which is why his June 23 lawsuit seeking class action status and unspecified damages against Plains All American Pipeline may prove to be a turning point in the sorry history of the Refugio oil spill.
"It was a disaster waiting to happen again and again," is the way Cappello described the badly corroded pipeline that gave way on May 19, spilling roughly 100,000 gallons of crude oil, sending about 21,000 gallons down a culvert and into the ocean. His lawsuit, filed on behalf of Pacific Coast property owners, states: "While this spill is a disaster it is no accident."
Cappello is the former Santa Barbara city attorney who sued Union Oil after the 1969 oil spill that devastated the coast and provided much of the impetus for the environmental movement. Over the years he's litigated on behalf of a number of corporate clients and recently forced the city of Santa Barbara to abandon its at-large city council election scheme on the grounds it was disenfranchising Hispanic voters.
In a phone conversation about the Refugio spill, Cappello said that Plains' failure to provide automatic shut-down devices for Line 901 is at the heart of his case.
The lawsuit alleges Plains "wantonly disregarded the safety of the people and environment by operating a pipeline it knew did not have proper safety systems in place."
Plains did not respond to requests for comment addressed to its Texas headquarters and Refugio Spill Unified Command response center.
Among the remedies Cappello seeks is a court order that requires Plains to install the automatic shut-off devices that Plains circumvented in the late 1980s when it went to court and won the right to have the only pipeline in Santa Barbara County regulated only by the federal government.
"It's too late" to halt the damage from the May spill but Cappello said he hopes to convince a judge to "eat the capital cost" of operating safely. "Plains has an ugly 'tradition' of operating pipelines that fail," the lawsuit alleges, stating that the company's way of doing business shifted the risk of environmental damage onto the shoulders of Santa Barbara's "citizens, real property owners and environment" while the company reaped the rewards.
Cappello's lawsuit is on behalf of a trust that owns property near Refugio State Beach and it seeks class action status to represent several thousand property owners along the Pacific Coast.
Already tar balls have washed up on beaches in Ventura and Los Angeles counties and Cappello thinks that more oil will wash up on California beaches over the next "three or four years."
His lawsuit is likely to get some traction for several reasons. First, the damages suffered by landholders are likely to be more sustained and easier to prove than those suffered by fishermen whose grounds were reopened on June 29.
Second, the properties involved are worth billions of dollars so that even temporary disruptions via tar ball intrusion can be quantified and the number of plaintiffs will likely grow.
Third, although Cappello said he hasn't talked to law enforcement about the evidence he has gathered, there is a parallel criminal investigation being conducted by Attorney General Kamala Harris and Santa Barbara County District Attorney Joyce Dudley. Whatever the criminal probe turns up will benefit Cappella's case and vice versa — putting Plains in a bit of a legal vise.
Meanwhile, yet another potential legal problem is looming for Plains as operations shut down and ExxonMobil and Venoco among others have no place to ship their oil.
That's because in addition to shutting down Line 901, the June 3 order by Jeffrey Weise, associate administrator of the Department of Transportation's Pipeline and Hazardous Materials Safety Administration has shut Line 903, which connects to the shorter pipeline that ruptured on May 19.
Pipeline 903, which runs 128 miles from Santa Barbara to Kern County, remains shut until Plains proves to the government that it can be operated safely. Even if it can re-open, volume is likely to be limited to 80 percent of average capacity over the past few months and other restrictions are likely to apply.
Every day they can't move oil through to Kern County, the oil companies also are tolling up economic damages. My guess is those will also cost Plains a pretty penny.
So far, Plains is hanging tough, stating in SEC filings that it simply can't quantify total costs, including possible civil and criminal claims. Cappello said that while he's filed the suit he hasn't served Plains — a development expected in the next week or two.
Perhaps then we'll get an answer from the company. But I'm not holding my breath.
• Reach Editor Dubroff at [email protected]
Drought will make water pricey, stymie development
Vintners decry proposed changes to Santa Barbara County winery ordinance
Real Estate: Investor pays $3.4M for Ventura building in hot industrial market
Wednesday, December 22nd, 2021
A Caruso mayoral bid could be another 1990s throwback in LA
SoCalGas feels pressure on its plans for West Ventura compressor station
In this COVID wave, businesses must make their own public health decisions
Women continue to bear economic brunt of pandemic, especially in California
New CEO brings 'grower's perspective' to Ventura County Farm Bureau
Region sees uptick in retail crime
Guilty pleas in perfume thefts as Ventura County authorities take action on retail crime


text:
Teimuraz Gabashvili fue el campeón defensor, pero decidió no participar este año.

Karen Jachanov derrotó en la final a Rubén Ramírez Hidalgo.

Cabezas de serie

 ' Karen Jachánov (Campeón)
  Radu Albot (Cuartos de final)
  Amir Weintraub (Cuartos de final)
  Jordi Samper (Segunda ronda)

<ol start=5>
  Farruj Dustov ''(Primera ronda, retiro)
  Dmitri Popko ''(Segunda ronda)
  Nikola Milojević ''(Primera ronda)
  Enrique López Pérez ''(Primera ronda)

Cuadro final

Cuadro superior

Cuadro inferior

Referencias
 Cuadro principal
 Cuadro clasificatorio

Challenger de Samarcanda 2016


text:
Area news in brief
Former cop, accused of rape, faces trial
THIBODAUX � A former Assumption Parish Sheriff's deputy accused of kidnapping and raping women motorists while on duty is one step closer to trial.
Michael Pintado is scheduled for a Nov. 23 pre-trial hearing in Judge Alvin Turner's Napoleonville court.
Pintado was arrested June 13, 2008, for allegedly kidnapping and raping a woman suspected of driving drunk on La. 1 in Labadieville three days prior. Days later, two additional women made similar allegations against Pintado.
Pintado was indicted by a grand jury Oct. 8 on charges of sexual battery, kidnapping, obscenity, battery and malfeasance in office, all charges stemming from his June 13 arrest.
They also indicted him on an additional count of malfeasance in office for another accusation that allegedly occurred Jan. 1, 2008, while he was working in Pierre Part.
If convicted of all charges, Pintado faces up to 33 years in prison.
Help give
HOUMA � The Sunrise Rotary Club of Houma is collecting new and used bikes that will become Christmas gifts for children whose families can't afford them.
You can donate as an individual or organize a company-wide drive. The bikes can be dropped off at any Coastal Commerce or Synergy Bank branch. Or Rotary Club members will pick them up.
"The needy kids in our community will thank you with a big smile when they get a bike for Christmas," says a letter from the club announcing the drive.
For information, call David Rabalais at 804-4650.
Find fresh food at
the Farmers' Market
THIBODAUX � Looking for fresh fruit and vegetables to spruce up your meals? Visit the Thibodaux Main Street Farmers' Market, held Saturday mornings near downtown.
Hours are 7 to 11 a.m. at the Jean Lafitte National Park, 314 St. Mary St.
Prospective vendors can call 448-1474 for information.
Your input on grant money is needed
THIBODAUX � Residents looking to offer suggestions on how $36 million in Community Development Block Grant money should be spent in Lafourche are invited to attend one of three upcoming public hearings.
The meetings start at 6 p.m. at:
n Tuesday, Moses Community Center, 1310 Cardinal Drive, Thibodaux.
n Wednesday, Government Complex, 4876 La. 1, Mathews.
n Sept. 3, Cut Off Youth Center, 205 W. 69th St.
Qualified projects include housing, community development and renovations to the old Wal-Mart in Mathews, now serving as Lafourche government headquarters and called the Mathews Government Complex.
Firefighters can
solicit on streets
HOUMA � Terrebonne Firefighters can now stand on street corners two weekends a year and collect donations for the Muscular Dystrophy Association.
The Terrebonne Parish Council approved the street-side solicitations by a 5-4 vote Wednesday, making an exception to the parishwide ban on such activity. Council members Joey Cehan, Teri Cavalier, Clayton Voisin and Kevin Voisin voting against it. Cehan said money can be raised through other events and activities, and Clayton Voisin said he fears this will open the door for other charities and organizations to make the same request. And traffic could become dangerous if drivers begin abruptly stopping or holding up traffic to pay the firefighters, Councilman Kevin Voisin said.
"We got rid of these for a reason," he said.
But these organizations make people's lives better, Councilman Alvin Tillman said.
"This is a no-brainer," he said, describing them as "angels." "Until you're touched by an angel, I don't think you can understand the magnitude of what those families in need are talking about."
Parish to collect more property taxes
HOUMA � Despite pleas from a handful of residents to collect less in property taxes this year, the Terrebonne Parish Council unanimously approved collecting an additional $262,000 at its regular meeting Wednesday.
The bulk of the increase will be paid by taxpayers in Houma for the city's police and fire departments and by taxpayers in various road-lighting districts to pay for street lights.
"The people of Terrebonne Parish need you to understand that times are difficult," said Houma resident Kathy Burson. "This is your opportunity to tell them you're on their side."
Though an increase in collections, the parish is still at or under the millage rates approved by voters. parish officials said.
In 2008, the parish collected $36 million through roughly 30 taxing districts to pay for roads, road lighting, sewers, recreation, drainage and fire and police protection in Houma. This excludes the rural recreation and fire districts that have separate governing boards to set and collect their property taxes each year.


John Conklin (born June 22, 1937) is a theater designer and teaches in the Department of Design for Stage and Film at New York University's Tisch School of the Arts.
Donald Oenslager (March 7, 1902 - June 11, 1975) was a celebrated American scenic designer who has won the Tony Award for Best Scenic Design.
Oliver Smith (February 13, 1918–January 23, 1994) was an American scenic designer.
Adrianne Lobel is an American scenic designer and producer for theatre, opera, and dance known for her "very daring and creative sets."
Harriet Burns (August 20, 1928 – July 25, 2008) was an American artist and designer. Burns was the first woman hired in the Walt Disney Imagineering department within the Walt Disney Company.
Boris Aronson (October 15, 1898 – November 16, 1980) was an American scenic designer for Broadway and Yiddish theatre. He won the Tony Award for Scenic Design six times in his career.


Two weeks away from the general election, on the first day of early voting, the two candidates for governor staked out Beaumont and drew clear lines between their campaigns.
At Madison's on Dowlen, U.S. Rep. Randy Weber introduced Republican Greg Abbott, the state attorney general, as a "true freedom fighter" for "gun rights, religious rights and states' rights."
At the Solid Rock Community Church on Pine Burr Road, Davis reacted to Weber's description of Abbott.
"Interesting choice of words," she said. "He's working against it with the state's voter ID law."
Early voting began on Monday and continues through Oct. 31. Election day is Nov. 4.


text:
Celebrating 45 Years With Mr. Coffee
Learn the vital role Dave Buck played in the company's first products
In 1972, Dave Buck was like many college students, just trying to determine what he wanted to do in life. Mid-way through his junior year, he decided to make a change. So he hitch-hiked from Detroit to San Francisco via Route 66 and finally back to Cleveland to be closer to his twin brother. He soon heard (from his now sister-in-law) about a new company holding open interviews. He showed up, interviewed and was hired as the 15th employee of an unknown start-up, created under North American Systems (NAS) owned by Samuel Glazer and Vincent Marotta, called Mr. Coffee. It was launched to recreate the coffee house experience at home using an automatic drip coffeemaker patented by Edmund Able, a self-taught engineer who became a mentor to Dave in the early years of his career.
In his first position, before there was a production line, Dave spent two weeks hand-molding and bending 5,000 heating coils that went into the first Mr. Coffee home brewing machines. Fast forward 45 years - Dave has since held positions in production, procurement, sourcing and product development, just to name a few, all in support of the Mr. Coffee brand.
"And it's been an adventure ever since," Dave said. From the first cup of "high test" coffee in the morning to riding his bike into the office, he's always remained enthusiastic about a career that speaks to his passion: sharing a cup of coffee with the people in his life.
"[Riding my bike to work] keeps the blood flowing, keeps you active," he said. "It puts the energy that you get from that first cup of coffee to use."
Dave's had the opportunity to watch the company grow from a single production line in a small building, to a 900,000 sq. ft. space in northeast Ohio. Shortly before Christmas in 1972, Mr. Coffee set a record by producing 1000 coffee makers a day. By the end of 1975, they were producing 40,000 a day.
I saw the effort of so many people working to one common goal. When you build something, when you're a part of that, and know you are among the first to come on board, you become part of this story. And being a part of that success has always fired me up.
In 2000, Dave moved to South Florida after Mr. Coffee was acquired by Sunbeam. "Some of the best, most rewarding years of my career have been here in South Florida," he said.
Today, Dave loves that his position as a Senior Manager in Product Development Engineering allows him to collaborate with other teams like Brand Marketing and Industrial Design to concept, execute and bring a product to our consumers.
"There are some really sharp, energetic, enthusiastic young people here. There's an energy you get by being in that kind of environment," he said. "Sometimes when you know what you know, you get a little stuck until somebody says, 'What if we did this?' and it kind of wakes you up a bit and you think to yourself, 'Yeah, why not!'"
Maintaining that enthusiasm and always moving forward through innovation, design and staying ahead of the competition has contributed to the success of the brand and Dave's loyalty to the company.
"It all has to do with the continued embrace of the consumer to coffee," he said. "That's what seems to have the fairy dust sprinkled on it."
Since Mr. Coffee has become a part of Newell Brands, there's been a whole new level of excitement in his career, Dave shared.
"When I think about retiring, things seem to get more exciting, another layer of fun is added on" he said. "We're just at the start of this new adventure."
The very first Purchase Order for Mr. Coffee Makers sold to Hammacher Schlemmer. Guess who hand molded the heating coils in all 144 units?
Careers#LiveAppliances & Cookware
Brands featured in this story


A make-over for the door to my studio. I was going through some of my stash in the basement when I came upon a couple of old painted canvases from maybe 25-30 years ago, and it struck me that sections of them would look good on the outside of the door to my studio. Box cutter in hand, I went to work cuttting out a couple of smaller rectangular pieces from the larger stretched canvases. Then I grabbed a bucket of matte medium, a large brush and a roller and went to work gluing the sections to the door. What fun! This is a work in progress and next I'll be painting the abstract shapes freely drawn with a broad-tipped sharpie around the edges. Who knows what else I may add before I proclaim it finished. Never fear. I'll keep you posted.
Thanks, Tracy. Not sure Betsy likes it. She's planted morning glories to grow up my security door.


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DRIVE AWAY PRICE
BASIC SPEC
07 Oct 2016 Toby Hagon With David Morley
4.5litre
1 reading now
Supercars compared: Ferrari v Lamborghini v Porsche v Mercedes-Benz
They're sexy, desirable and beyond the reach of most people. But if you had to choose, which of these beauties steals your heart? Toby Hagon reports.
$2 million worth of exclusive supercars are compared to determine which one is the ultimate dream car. Photo:
Ferrari's 458 Italia has a top speed of 325km/h. Photo:
Ferrari 458 Italia interior. Photo:
The Mercedes-Benz SLS AMG 'Gullwing' has a top speed of 317km/h. Photo:
The Mercedes-Benz SLS AMG 'Gullwing' interior. Photo:
Lamborghini's Gallardo LP550-2 has a top speed of 320km/h. Photo:
Lamborghini Gallardo LP550-2 interior. Photo:
Porsche's 911 Turbo has a top speed of 312km/h. Photo:
Porsche 911 Turbo interior. Photo:
(1) Reading now
Ask a schoolchild to name their dream machine — if it's not a fire engine or a police car, there's a fair chance it will come from an Italian or German supercar maker.
Yet while head-turning style and low-slung looks may entice future generations, it's what's under the bonnet (or, in some cases, behind the occupants) that defines a supercar.
They don't get much sexier — or faster — than the quartet of cars playing supermodels for a day in our abandoned warehouse. Under bright lights, our Ferrari, Lamborghini, Porsche and Mercedes-Benz still manage to look poised to break the speed limit even when they're not moving.
Between them there's a combined 1618kW of power (more than that of a dozen mid-sized cars), 27 gears and 32 cylinders.
But they seat only 10 people and will set you back almost $2 million — about a quarter of which goes to the government in taxes.
Drive cover
Heading the field is arguably Ferrari's best-looking car, the new 458 Italia. Even before the first one arrived here, the supercar — worth upwards of half a million dollars — had already sold out for 18 months.
No less head-turning is the Mercedes-Benz SLS AMG, better known as the "Gullwing" for its top-hinged doors that open up rather than out. Its beefy V8 is almost as audacious as its retro-infused styling, while its supercar price tag is almost 15 times that of the most affordable Mercedes-Benz.
From Porsche, it's the turbocharged 911, one of 20-odd models in a range that starts at more than $200,000 and tops out at almost triple that. The Turbo teams a wider body with all-wheel-drive and twin-turbochargers for explosive performance.
Rounding out the field is the latest variant of Lamborghini's wedge-like Gallardo. The LP550-2 eschews some equipment (including the all-wheel-drive system) and aims for performance on a budget, relatively speaking.
City lights: Suzuki Alto v Holden Barina Spark v Nissan Micra
Mercedes-Benz SLS AMG 'Gullwing'
For something a bit different
Seven-time formula one world champion Michael Schumacher had — or has — something to do with half the field. He was instrumental in tuning the Ferrari 458 Italia and, after switching to Mercedes-Benz for formula one, he drove upside-down in a tunnel to promote the Gullwing.
Porsche's claim to development fame is no less effective. Former dual world rally champion Walter Rohrl, responsible for ensuring Porsches live up to their performance expectations, has also set the all-important lap times around the famed Nurburgring circuit.
For Lamborghini, its test driver of 40 years — Valentino Balboni — is the only one with a model named after him, having retired from the Italian maker in 2008. The LP550-2 in this test is the same car mechanically, albeit without some of the stripes and other extras.
So, when you retire — or grow up — which supercar would you want to power around in?
For more on these cars, go to drive.com.au/exotic
Supercar comparison
Interested in buying Ferrari 458 Italia? Visit our Ferrari showroom for more information.
Go behind the scenes on Drive at Facebook, Instagram and YouTube
Ferrari 458 Italia Summary See other Ferrari 458 Italia models
2 seater Coupe
Drive Ratings
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text:
layout: page
title: Alvarez Tone Llc. Seminar
date: 2016-05-24
author: Rebecca Lee
tags: weekly links, java
status: published
summary: Aliquam et justo dui. Proin accumsan.
banner: images/banner/meeting-01.jpg
booking:
  startDate: 10/10/2018
  endDate: 10/14/2018
  ctyhocn: FTWWTHX
  groupCode: ATLS
published: true
---
Duis sed libero pharetra, egestas purus eu, euismod purus. Duis placerat nibh sed ipsum mollis, quis rutrum urna auctor. Aenean vel leo eu dolor placerat maximus. Fusce sollicitudin et elit sed interdum. Sed diam orci, iaculis quis posuere non, posuere a odio. Nunc auctor ipsum a augue posuere, sit amet rutrum arcu gravida. Praesent mattis iaculis tempor. Nunc in mollis elit, vitae vestibulum leo. Integer vel pulvinar quam. Proin a lacus orci. Proin nec viverra orci. Donec efficitur sem eu mollis pretium. Nulla nec bibendum lorem, sed eleifend ipsum. Vivamus posuere magna et ligula iaculis ullamcorper. Cras tincidunt ante sed ligula sollicitudin, in pellentesque nisl vulputate. Pellentesque scelerisque cursus libero quis efficitur.
Morbi maximus dictum mi ac scelerisque. Morbi ut eleifend enim. Sed ut interdum felis. Duis dapibus posuere orci ut porttitor. Donec luctus condimentum maximus. Pellentesque elementum nibh orci, sed tincidunt magna elementum in. Morbi porta ligula viverra, dictum nulla id, sagittis mi. Cras quis mi vel orci finibus tempus. Aliquam egestas tincidunt nisi nec lacinia.

* Duis euismod justo vitae dictum dignissim
* Phasellus lobortis purus quis orci sollicitudin, vel lacinia turpis lobortis
* Proin in odio maximus, aliquam tortor a, lobortis augue
* Morbi posuere libero id dui finibus, at posuere magna pretium.

Fusce consequat, ligula sed dictum scelerisque, lectus est porta dui, sit amet iaculis tellus augue eget mauris. Sed tempor ipsum eget orci convallis pellentesque. Vestibulum egestas lectus vitae massa efficitur, in blandit dui vestibulum. Praesent id vulputate enim, quis molestie lectus. Vestibulum nec odio nibh. Cras semper, augue vitae sagittis ullamcorper, tellus ex pellentesque metus, sit amet scelerisque justo mauris dignissim lectus. Sed a maximus lorem. Nullam eu sodales tortor, vitae aliquet ex. Donec quis lacus urna. Nunc lorem ligula, imperdiet vitae congue eget, auctor et nibh. Donec eu congue ligula. Proin a leo pharetra, pellentesque augue ac, rhoncus ligula.

redpajama_set_name: RedPajamaGithub


Pitch your tent or bring your camper or RV and enjoy the beautiful view across the valleys gorgeous sunsets and lots of Texas Longhorn. Lots of trails private roads to walk on as well as fishing and hiking through the woods . Come back and enjoy a campfire at the ranch pavilion. All year round camping is available .
Must clean up after pet.
Full hook up sites, even for big rigs. 30/50 amp, sewer, water, trash, bathhouse. This is a working Texas Longhorn ranch.
Have a question? Send Bryce a message!
Natural features you'll find at CF Ranch and Cattle Company in Ohio.
If you've fully explored and read the information on this listing page and still have questions, you can message Bryce here.


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Of course, the first thought that comes to everyone's mind when someone mentions English theatre is that it is the land of Shakespeare. Yet, the English stages are rich in other theatrical treats, from unique theatre architecture and brilliant venues to innovative playwrights and directors. You can see charming unpretentious plays in small, lovely theaters, or you can go for the huge stage productions. In London you can basically find anything – and if you are lucky, you might even get to see some very famous names like Ian McKellen and Richard Armitage rocking the stage. So, what path should you take if you want to experience the authentic English theatre? Here's what you need to know.
The early beginnings of theatre came to England with the Romans who introduced their auditoriums to Britain (and mind that much of the Roman theatre was inspired by the Greeks, who invented this noble art). Up to the Medieval times, English theatre was far from what we perceive as theatre today but it was still exciting. It mainly consisted of mummer's plays and things like Morris dances, i.e. dances that were performed by groups with swords. Shakespeare had to wait for a few more centuries to get up on the stage but the people of that time were certainly satisfied with the repertoire.
From around 1350, theatre gained huge popularity in England. This mainly had to do with the fact that the church took quite an interest in using theatrical plays as a way to spread their message. Theatre was seen as a great tool of explaining Christianity to ordinary people, with many of them still being illiterate and unable to read religious books. People took to it well. After all, it was a nice break from their everyday life, it was an act of bringing the community together, and many of the plays were actually quite entertaining. You see, "edutainment" is not exactly a modern thing. The church knew how to do it in the middle ages!
Henry VIII (who reigned over England from 1509 to 1547) was a man who cared for his leisure time and wanted to spend it having fun. The court entertainment, as another theatrical form, became highly important. Religious plays, on the other hand, suffered quite a bit because of the Reformation. Secular drama became dominant, and while plays in the past had often been performed in mobile wagons or in big halls in the homes of the rich and royal, the 16th century saw the emergence of the first proper playhouses in England. The first playhouse was built outside the city walls of London as London was not that keen on public performances yet.
The late 16th century is often seen as a vital period for English theatre. It was the time of playwrights like Shakespeare and Christopher Marlowe, whose immortal verses became one of the cornerstones of modern writing. Interestingly, the writers of these times were also very prolific, as their theatre companies were performing up to 40 new plays each year. Some personal dramas were also in the game, as different companies engaged in some serious rivalry, and the main actors also had shares in the theatres – so the more popular their plays were, the more they also earned. Minor actors were only paid on a weekly base. Theatres also worked with young boys, needed to play female roles, who received only some pocket money as they were only seen as apprentices.
In 1599, the famous Globe Theater was erected. Up to three thousand people could see the plays in this new theatre, and today it is mainly well-known because some of Shakespeare's most famous and most popular plays were written for this theatre. Don't confuse 1990 reconstruction of the Globe with the original – the new Globe, however, is a poignant way of honouring Shakespeare and Elizabethan theatre.
Shakespeare died in 1616, and unlike many of his contemporary writers, he lived a life with relatively little scandals. He might have been too busy focusing on his writing – or he might just have been better at keeping his secrets secret. Maybe his secrecy brought us into today's situation when we are questioning his true identity. Whatever the story behind Shakespeare's name is, his plays are one of England's most precious legacies.
During the civil war, theatres were closed for eighteen years, as it was feared that these venues could be places for civil unrest. During the restoration, theatres in England changed once more – one very notable change was that female playwrights were finally also accepted. In the following centuries, theatres became even more popular, more and more proper venues were built, and quite a few people could make a living with being actors or playwrights alone.
One might assume that theatre does not play such an important role in modern England anymore – after all, there is a lot of competition for theatres in the form of cinemas, TV, concerts or computer games. However, when you pick up any copy of magazines in London that tell you "What's up in London" (or any other bigger city in England), you will always see that theatre plays still hold a vital role in the entertainment scene in England. Some of the world's most important theatre names in the past few decades have emerged in England (Sarah Kane probably rings the bell), proving that our stages still care about being relevant.
Small troupes and alternative venues make English theatre even more dynamic. Virtually everywhere you go, you can get the thrill of the enthusiastic independent productions or community theatres. Whether you choose ambitious and expensive productions of classics, independent interpretations of Shakespeare in cool alternative venues or debut plays by upcoming playwrights, you will have plenty on your table!


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Christoph Wilhelm von Kalckstein (17 October 1682 – 2 June 1759) was a Prussian count, field marshal, teacher and educator of King Frederick II of Prussia.

Military career
Kalckstein was born in Ottlau near Marienwerder, Ducal Prussia, to Christoph Albrecht von Kalckstein, laird of Knauten, Wogau and Schloditten near Pr. Eylau, and Marie Agnes von Lehwaldt. He was the grandson of Albrecht von Kalckstein and nephew of Christian Ludwig von Kalckstein, former opponents of Frederick William, Elector and Duke of Brandenburg-Prussia.

Kalckstein joined the Hesse-Kassel Grenadier Regiment in 1702, taking part in the War of the Spanish Succession in 1704 and becoming adjutant of Prince Frederick of Hesse-Kassel, the later King Frederick I of Sweden. In 1709 Kalckstein entered the Prussian Army and became a Major in the King's own Regiment (Leibregiment zu Fuss). In 1712 he conquered the citadel of Moers with only 300 men and fought against Sweden in the Great Northern War in Pomerania in 1715. He was promoted to a lieutenant colonel on 15 November 1715.

Educator of Frederick II of Prussia
After his promotion to a Colonel on 17 August 1718, Kalckstein was assigned as the educator of the Prussian crown prince, Frederick. In this position he became a  conciliator in the conflict between King Frederick William I and his son.  However, he was ordered to keep a strict watch on the crown prince. After his wife, Christophera Erna Lukretia Brandt von Lindau, died on 25 January 1729, he was released from this position.

Later career
Kalckstein became the Commander in Chief of an Infantry Regiment, Major General on 2 May 1733, and Lieutenant General on 3 February 1741. After 5 November 1736 he was the supervisor of the Charité hospital in Berlin. In the Silesian Wars he fought at Mollwitz, Chotusitz and Hohenfriedberg, became the Governor of the Fortress Glogau, and received the Order of the Black Eagle. On 24 May 1747 he was appointed the rank of a Generalfeldmarschall.

After Crown Prince August William died in 1758, Frederick II appointed Kalckstein as a custodian and educator of the later King Fredrick William II and his brothers.

Kalckstein died in Berlin and was buried at the Berlin Garnisonkirche (Garrison Church).

References
 Horst Schulz, "Der Kreis Pr. Eylau", Verden/Aller 1983, p. 765
 Joachim Engelmann: Friedrich der Große und seine Generale. Friedberg 1988.
 Allgemeine Deutsche Biographie Bd.15, S.17-18

1682 births
1759 deaths
Field marshals of Prussia
German untitled nobility
People from the Duchy of Prussia
Prussian Army personnel
German military personnel of the War of the Spanish Succession
People from Kwidzyn County


We interviewed Linda to ask her all about her summer plans and let's just say she is definitely taking advantage of what the Pacific Northwest has to offer!
Fresh seafood – coppo river salmon, local clams, and oysters to name a few!
What is your favorite outdoor activity under the sun?
Do you have any recipes you particularly like to make during this season?
With leftover smores goodies, make either a portioned controlled individual smore or pan of smores by crushing the graham crackers and placing them in the bottom of a ramekin or pan. Top it with either hot fudge sauce or leftover chocolate pieces and place a marshmallow on top! Heat in the oven until the marshmallow is toasted and gooey. Cool slightly and enjoy!
-Yum Linda, thanks for the suggestion!
Staff trip to Whistler, BC, Canada… stay tuned to see our adventures!
What is your goal? How might you achieve it?
Exercise more – get outdoors!
All in all it looks like Linda lives a wholesome summer and has plans to continue having a great one! One common theme we see here and previously in both Anna's and Sophia's is that they all want to enjoy the beautiful summer that the Pacific Northwest offers! Linda takes advantage of that by attending farmer's market for fresh, local goods and spends an array of time being outdoors and active. Can you relate? Let us know in the comments below!


text:
Best Online Singing Lessons
The 6 Best Wireless Microphone for Singers [2019]
How Much is Dionne Warwick's Net Worth?
Dionne Warwick is an American singer and actress with a net worth of -$10 million. Dionne filed for bankruptcy on March 21st in New Jersey after discovering that she owed more than 10.2 million in taxes. According to her publicist Kevin Sasaki, the legendary singer cited fiscal mismanagement as the main reason she owed so much to the point of being broke. Dionne believes that most of the supposed negligent and gross financial mismanagement occurred in the late 1980s through the 1990s when she was still active career-wise.
Dionne Warwick listed her average monthly income as being just $20,950, with expenses totaling $20,940. As Sasaki puts it, Dionne had reportedly paid back her taxes and that what she owed amounted to interest that accrued on those taxes. Sasaki said that when the authorities notified her about the extent of her tax liabilities, she repeatedly attempted to offer re-payment plans and proposals to the IRS and the California Franchise Tax Board for taxes owed. They however rejected these plans which resulted into escalating interest and penalties.
Bankruptcy Problems
Dionne Warwick's bankruptcy counselor Dan Stolz, also confirmed that she owed an accumulated amount worth $10 million. Stolz said that this was as a result of payments Dionne made over the years which were then applied to interest and penalties instead of the principal amount. He stated that Warwick should expect no trouble to emerge from her current situation. This is because congressional bankruptcy codes allow for the discharge of income taxes that are more than 3 years old.
According to Stolz, Dionne Warwick's predicament was caused by a bad business manager who ran her into debt but was fired several years back. There were also reports that the IRS had lost Dionne Warwick's files for several years. The same IRS stated in 2009 that Dionne owed $1 million and according to Stolz, the legendary singer had already paid about $1.3 million over the years which is more than what she owes in tax.
Of course Dionne Warwick isn't the only celebrity plagued by money problems. Renowned celebrities like Mike Tyson and Toni Braxton have also declared bankruptcy. Many other celebrities have also experienced some sort of financial woes.
Dionne's Past and Rise to Stardom
Born in East Orange, New Jersey, U.S Dionne Warwick originally attained stardom status as both a singer and songwriter. She also had a long-lasting partnership with Burt Bacharach and Hal David. Apart from her singing career, Dionne also served as the United Nations Global Ambassador for the Food and Agriculture Organization (FAO) and as a United States Ambassador of Health. According to the Billboard Hot 100 Pop Singles Charts, she was one of the 40 biggest hit makers of the entire rock era (1955–1999). Dionne Warwick is second only to Aretha Franklin as the female singer with the most singles on the Billboard Hot 100 chart. She has won 5 Grammys, including awards for hits such as Do You Know the Way to San José, That's What Friends Are For and I'll Never Fall in Love Again. In That's What Friends Are For, she featured Stevie Wonder, John and Gladys Knight. Other popular hits she released include Raindrops Keep Falling on My Head and The Look of Love.
Click here for a full write-up of Dionne Warwick's Biography.
30.10.2018 14:44 Can Singing Lessons Improve Your Voice?
30.10.2018 14:43 What Age Should Voice Lessons Start?
30.10.2018 14:42 How Much Does it Cost for Singing Lessons?
30.01.2017 09:19 Best Dionne Warwick Hits of All Time
12.01.2016 19:00 The Kennedy Center and Georgetown University present Let Freedom Ring! featuring Dionne Warwick
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text:
Rep. Vela Introduces Bill to Add Fort Brown to Palo Alto Battlefield National Park
WASHINGTON, DC – Today, Congressman Filemon Vela announced the introduction of legislation to amend the law which established the Palo Alto Battlefield National Historical Park to include the historic Fort Brown site in Brownsville. The fort was a crucial location during the Mexican-American War and was designated a National Historic Landmark in 1960. The bill would authorize the transfer of property from the IBWC (International Boundary and Water Commission) Tract 10 to the National Park Service to be part of the Palo Alto Battlefield, which also includes Resaca de la Palma Battlefield unit.
"Preservation and protection of historic sites like Fort Brown will help ensure public access to locations of significance to the United States, the state of Texas and the City of Brownsville," said Vela. "As Brownsville's federal Representative, it is my honor to work with the National Park Service and the local community to expand the Palo Alto Battlefield National Historical Park."
Permalink: https://vela.house.gov/2019/7/rep-vela-introduces-bill-add-fort-brown-palo-alto-battlefield-national


There's no way to get around it: death is not a pleasant topic of conversation. However, loss does happen and when it does, it's crucial to know that the people who depend on you are taken care of. That's why an experienced and unbiased research team spent months analyzing 67 life insurance companies to help single parents. Their goal was simple: determine the most reliable and smartest options that can help offset funeral costs, ensure stability for dependents, and create some semblance of peace of mind. Ultimately, they created a guide that helps walk people through the process of purchasing life insurance, highlights the different factors they should consider, and translates all the confusing terminology. You can see the guide here: www.reviews.com/life-insurance/ I hope that this research would be a useful resource to you; navigating this overwhelming industry isn't easy — especially for those of us who already have enough on our plates.
What is the Good of a Good Divorce?
Being a mediator for over 12 years, I often ask myself a question: what is the "good" of a good divorce and why is good ending valuable even when couples don't have children and presumably will never see each other again following their divorce? What can mediation give to couples besides the obvious benefits of being much less expensive and time consuming? I believe that good ending can bring forth a good beginning. Couples in mediation, while negotiating over their divorce agreements and trying to find reasonable compromises, often reflect on what went wrong and why. This causes them to contemplate on how they can change their situation in the future for the better. If they can sort out some of their issues while they are in mediation, they are less likely to repeat the same mistakes again. To me this is a huge benefit One of my clients once said to me on their last mediation session: I feel like we could have stayed married if we'd communicated with each other as we do now in mediation. I thought to myself that they could have stayed married should they have learned to communicate earlier and thus become a people they are transforming into now by getting a divorce.
What can be done to minimize the pain of divorce for your children?
As I have written in my earlier blogs, children will have negative reaction to their parents' divorce. How to minimize their pain will depend on how divorcing couples handle their divorce situations and how they behave, especially in front of their children. Children need to understand what is going on so they don't feel "left in the dark" and out of control. However, they don't need to know every dirty detail and every angry remark you make while you are being separated. Provide truthful information which is age appropriate, emphasize that divorce is not their fault and that your love for them will not change. Do not bad-mouth the other parent to your children, even though you may feel angry and frustrated with him/her, and even though you absolutely truly believe that your ex-partner is totally in the wrong. When you do bad-mouth, children feel that they need to take sides and that increases their feeling of guilt. Another trap many divorcing parents fall for is that they use their children as confidantes. Doing that will make your children feel guilty towards the other parent. Also this way you may overburden them with the information that they absolutely do not need and thus increase their already high stress level. It is a very good idea to consult with a mental health professional on how to help your children cope with your divorce, especially if you feel that the situation gets out of control. If both parents can work with the same mental health professional to minimize their children's pain and stress, that would create a more stable environment for them. Another very important tip for the divorcing parents is to be as consistent as possible, especially when it comes to visiting and keeping plans. Your children have just experienced a major loss in their lives. By keeping the routines going you help them to maintain some normalcy and equilibrium in their lives.
How children react and make sense of their parent's separation will vary depending on their age and stage of development at the time of their parents' divorce. Children younger than two or three years may have fewer negative effects, especially if the bond and close relationship with both their parents is sustained. Still babies do feel their parents' distress, might cope poorly with alterations and discontinuity in schedules and might also feel unprotected. Preschoolers (children three to five years of age) might blame themselves and believe they have caused their parents' divorce. At this age, children may fear being left alone or abandoned and for that reason might regress into a baby-like behavior. They might become uncooperative, depressed or angry. They will yearn for the absent parent especially if they do not see him/her very often. School-aged children (six to 12 years of age) will probably have the most difficult time coping with their parent's divorce. They are old enough to understand what is going on, but they are too young to comprehend or control their reactions to this pain. They will be torn between the two parents and feel forced to choose. Therefore, such feelings like shame, resentment, rejection, and anger are extremely common to the school-aged children at this difficult time in their lives. Adolescents will also experience anger, fear, loneliness, and depression. They will also worry about their financial security and their future plans. Some will be frustrated should they be made responsible for chores that were not part of their routine when their parents stayed together. They might question the marriage institution in general and their own ability and desire to get or stay married. No matter how old your child is, divorce will have a major impact on his/her life. Will your child have long lasting consequences? That will depend on how you end your marriage, how you build your life after divorce and how you deal with your ex-partner in front of your children. It is absolutely possible to raise happy and well-rounded children when you are divorced. It will take some hard work from both of you: but the results are certainly well worth it.