text:
\section{Appendix A}
Let matrices $A_{32}$, $B_{32}$ and $C_{32}$ are $N \times N$ matrices in FP32 and assume these
are well approximated by
\begin{align}
A_{32}  & \approx a1_{32} * A1_{16} + a2_{32} * A2_{16} \\
B_{32}  & \approx b1_{32} * B1_{16} + b2_{32} * B2_{16}
\label{eqn:A_1}
\end{align}
then $C_{32} = A_{32} * B_{32}$ can be approximately computed as
\begin{align}
C_{32}   \approx ~ & (a1_{32} * b1_{32}) * (A1_{16} * B1_{16}) + \\
                 & (a1_{32} * b2_{32}) * (A1_{16} * B2_{16}) + \\
                 & (a2_{32} * b1_{32}) * (A2_{16} * B1_{16}) + \\
                 & (a2_{32} * b2_{32}) * (A2_{16} * B2_{16})
                 ~.
 \label{eqn:A_2}
\end{align}
If we assume
$a2_{16} = 2^{-11} * a1_{16}$,
$b2_{16} = 2^{-11} * b1_{16}$,
then the last contribution is scaled by
$(a2_{32} * b2_{32}) = 2^{-22} * (a1_{32} * b1_{32})$
which may be optionally dropped without significant errors.
If so, then $C_{32}$ can be computed as 3 matrix multiplies in FP16.

\section{Background}

\vspace{-0.1in}
Deep learning (DL) has become one of the most prevalent technologies today. Applications extend from image recognition to natural language processing. While its commercial applications have garnered the efforts of major technology companies, DL has proven vital to works in numerous scientific domains.

Some of these domain problems are vital to solving many of today's global issues---for instance, in solving modern, data-dense problems in climate science. This field has seen several advancements with the recent integration of deep neural networks (DNNs). Ise et. al. \cite{10.3389/frobt.2019.00032} propose a modern approach towards utilizing neural networks to predict global temperature data. They further conclude that the accuracy of their model increases with the number of input images used. Thus, the model's accuracy and utility grow with the amount of compute power available. Wang et. al. \cite{gmd-12-4261-2019} provide further uses for DNNs in weather forecasting, which compete with the current state-of-the-art, physically based simulations. The neural networks can also reduce the computations necessary, as they possess the ability to extend one trained network to similar environments, or train once, and predict frequently.

Additionally, DL has proven useful in materials science, even leading the field of materials informatics \cite{agrawal_choudhary_2019}. Feng et. al. \cite{Feng_Zhou_Dong_2019} were able to utilize deep networks to predict material defects with an accuracy above 98\%, even for small data sets. However, these great accuracies require deep and/or pre-trained networks. As with climate modelling, deep learning can be used to replace current physically based simulations, which are expensive and/or do not scale well~\cite{Ye_Chen_Wang_Chu_Ong_2018}.

Providing high performance hardware and software stacks to facilitate deep learning has become a focus in the high-performance computing (HPC) field.  An overview of the parallel algorithms and their challenges for distributed, deep neural networks can be found in Ben-Nun and Toefler \cite{Demystifying-DL}. Large-scale modern systems, such as the US DOE's Summit, are fully loaded with high-performance GPUs to support the compute-intensive nature of deep learning. Additionally, some HPC distributed file systems under-perform in providing I/O for data-hungry DL training \cite{8890993}. Even in terms of sheer performance, many state-of-the-art deep learning models and libraries fail to utilize a significant portion of the maximum floating-point operations (FLOPs) rate of current top systems \cite{10.1145/3225058.3225069}. There is significant research in the area of accelerating DL on cloud and other commercial systems, but these methods may not integrate well with varying HPC technologies and modern scientific workflows.

One major area in which HPC can innovate deep learning is model parallelism. In many domain applications, networks can become large, leading to growth beyond the memory of a single GPU. By utilizing existing HPC communication standards, a robust model-parallel training standard needs to be developed in addition to efficient implementations. Currently, several libraries attempt to integrate model parallelism \cite{mesh-tf}, but this requires extensive knowledge of the code base, model, and hardware. There is an active research push into further developing model parallel approaches \cite{10.1145/3322795.3331463, Huang_Cheng_Bapna_Firat_Chen_Chen_Lee_Ngiam_Le_Wu, 10.1145/3210377.3210394, Chen2018EfficientAR}.

R. Stevens presented a vision of the landscape of machine learning as DOE moves towards the exascale era~\cite{RStevens:18}, stressing the importance of machine learning as an integral part of DOE exascale applications. The new paradigm of "HPC + AI" on exascale computing leads towards an "Integrated Sim, Data, Learn Stack." There has been a long history of application code development for compute-intensive applications in the areas of climate, materials, medical, high energy, and urban sciences applications. In light of these needs, we will highlight developments and discuss the necessity of a set of tools and methods particularly relevant to deploying AI on HPC systems.

Realizing the paradigm of ``HPC + AI" requires three major components: (1)~the HPC system and investments in scaling application-driven capabilities; (2) the AI software achieving the potential performance; and (3) the ``+", innovative algorithms and implementations/tools that combine the components of compute- and data-driven applications seamlessly on exascale machines.

\section{Deep Learning Software on Modern HPC Systems}

There are countless deep learning frameworks in existence today: TensorFlow~\cite{tensorflow}, PyTorch \cite{Paszke_Gross_Massa_Lerer_Bradbury_Chanan_Killeen_Lin_Gimelshein_Antiga}, MxNet \cite{mxnet:15}, and many others. Each framework has its own advantages and each falls short in some areas. One advantage of each of these frameworks is their strong corporate backings. Companies pour significant amounts of money into making production-ready libraries, which support various hardware. However, when using these frameworks in an HPC setting, this can cause issues. Much of the research and advancements by the library designers are production focused and target cloud environments. Some of these advancements translate well onto HPC systems, such as the use of hardware accelerators and mixed precision. However, many communication paradigms and implementations differ dramatically between the two. For example, the parameter server method in TensorFlow is more suited for heterogeneous cloud environments, although it is more bandwidth efficient than allreduce; and the socket-based GLOO communication backend built into PyTorch cannot efficiently utilize high-performance interconnects on HPC systems, although it is more flexible.

\subsection{Towards a Deep Learning Framework for HPC}
We evaluated a number of existing packages for their readiness to efficiently run deep learning models and applications on large-scale HPC systems. As	pointed	out previously, we	found various limitations. Our vision of what is important and needed in deep leaning AI packages for HPC is incorporated into the design of the MagmaDNN open source framework~\cite{10.1145/3332186.3333047,magmadnnISC19} (see Figure~\ref{fig:magmadnn}) with current release MagmaDNN v1.2~\cite{daniel_nichols_2020_3972406}, which we discuss briefly in what follows.

Firstly, MagmaDNN targets HPC systems, rather than cloud systems. It is written in C++ and is open source (available at \url{bitbucket.org/icl/magmadnn}).

Many of the core components of MagmaDNN are the same as other frameworks: operations are represented in a compute graph, data is passed around via tensors, gradients are computed using backpropagation, etc. However, each of these was designed with an HPC environment in mind.

\begin{wrapfigure}{r}{0.45\linewidth}
  \centering
  \vspace{-0.1in}
  \includegraphics[width=1\linewidth]{stack}
  \caption{MagmaDNN software stack.}
  \vspace{-0.2in}
  \label{fig:magmadnn}
\end{wrapfigure}

MagmaDNN is centered around existing high-performance software packages, enabling easy integration into existing environments and Exascale Computing Project (ECP) software products. First and foremost, MagmaDNN uses the Matrix Algebra on GPU and Multicore Architectures (MAGMA) \cite{magma} package for heterogeneous linear algebra, since deep learning is heavily dependent on linear algebra routines. For strictly CPU computations, the package allows the use of any Basic Linear Algebra Subprograms (BLAS)/LAPACK packages such as Intel MKL, OpenBLAS, ATLAS, etc.

To better operate with hardware accelerators, MagmaDNN uses CUDA packages to harness GPU acceleration. Custom CUDA kernels, along with CUDNN's routines for GPU-accelerated deep learning, allows the package to get maximal performance on GPU-enabled systems.

For distributed computing, MagmaDNN relies on existing HPC tools such as the Message Passing Interface (MPI) for its communication. Most systems have an MPI distribution tuned to that hardware, while some even have custom distributions. Relying on MPI for inter-node communication allows the framework to utilize existing optimized implementations while providing simpler integration with existing scientific codes.

This integration of existing HPC frameworks allows MagmaDNN to compile and link with the fastest libraries for particular hardware. Utilizing existing optimized packages is a consistent design pattern within HPC libraries, and MagmaDNN uses interfaces that are commonly installed on HPC clusters. In terms of integrating with existing systems and scientific codes, this approach offers the package a significant advantage over other frameworks and workflows.

Not only does MagmaDNN integrate with current HPC frameworks, it provides modularity in its design and linking so that users have flexibility in use. Conforming to standard APIs allows linking with any choice of framework; any BLAS/LAPACK/MPI choice implementations can be used. However, it is not just libraries with which MagmaDNN is modular. By utilizing computation graphs and extendable C++ classes, the package allows users to fully customize their neural networks. For instance, to utilize a unique network interface for distributed training, one can define a custom node on the computation graph which handles the transfer of data on that network component. This can be further utilized to define any desired data movement or computational elements. By providing modular components, MagmaDNN provides a structure onto which domain scientists can easily implement desired custom functionality.

Much of this customizability is fully supported through MagmaDNN's interfaces. For instance, working with GPU and distributed memory is abstracted away in the \verb|MemoryManager| class. Thus, library users do not need to worry about where memory is stored and how it is transferred. The package identifies the memory type, and whenever a memory operation is used (e.g., copy, put, get, etc.), and the MagmaDNN implementation handles the low-level specifics. Likewise, communication operations between devices or nodes are abstracted into the library as well. However, users can define their own operations, meaning they can redefine those in existing code. This makes it easy, for example, to try out different convolution algorithms and determine which one performs optimally. Another common example is to determine which distribution strategy is optimal for a specific machine. The same training code will run on any machine, and only the communication code might need to be altered.

Looking towards next-generation hardware and exascale systems, MagmaDNN aims to incorporate more technology stacks such as AMD's HIP (e.g., hipMAGMA is already available) and Intel's OneAPI. Support for more technologies will allow researchers at various labs and institutions to focus on domain research---and not on how to integrate their code with HPC stacks. We also hope to provide streamlined and optimal support for model parallelism. As the size of models grows, so does the necessary memory requirements on devices. Soon many cutting-edge networks, which can provide state-of-the-art accuracy in classification, will require model parallelism. Supporting fast, scalable model parallelism on HPC systems is crucial to facilitating next-generation research, and MagmaDNN is moving towards this goal.

\subsection{Workflow Software for Modern HPC Systems}

Another major component in the integration of AI and HPC is the availability of workflow software: which is critical, for example, in launching, collecting results from, and analyzing various simulations in hyperparameter tuning, DL networks discoveries, etc.
Exascale applications largely have their own set of workflow procedures and tools to launch their simulations. Integrating traditional applications seamlessly with existing AI software---either TensorFlow, PyTorch, or MagmaDNN---takes on a new level of challenges. Most workflow frameworks available today focus on cloud deployment, yet a workflow framework tailored to scale on HPC systems is critical to the success to "Automate and Accelerate" the task of "Sim, Data, and Learn Stack". SWIFT-T \cite{swiftt} is a tool that offers the choice to run on large-scale HPC systems. At The University of Tennessee, Knoxville (UTK), we have developed a parallel workflow framework called
openDIEL that aims to give researchers
and users of HPC machines an efficient way to coordinate, organize,
and interconnect many disparate modules of computation in order to effectively utilize and allocate HPC resources \cite{opendiel18,opendiel19}.
It provides users an adaptive avenue to run
compute-intensive and data science jobs concurrently, allowing specification of DNN architectures, data processing, and hyperparameter
tuning. Existing ML tools can be readily used
in openDIEL, allowing for easy experimentation with
various models and approaches.  Most importantly, openDIEL provides a platform to run existing ECP applications in their own workflow procedures.
When conducting multi-discipline simulations, it is often required
to use a large variety of software, and serial or parallel codes, to answer
a research question. Utilizing disparate modules of computation
requires the careful coordination of dependencies,
communication, and synchronization between them, and
there is not always a clear path.
This problem is solved by openDIEL: it enables
researchers to define complex dependencies between modules
and schedule communication between them.
OpenDIEL consists of three primary components: the workflow control
file, the communication library (COMMLIB), and the
Executive, shown in Figure~\ref{fig:minipage1}.
Workflow is defined by users via the control file, which consists of two parts, the definition of functional modules and the interactions and sequence of execution of modules. OpenDIEL provides two communication libraries, one for direct point-to-point data transfer between two modules, and a store-and-move tuple space library for collective and asynchronous data transfers. The Executive is a lightweight manager designed to run and scale on heterogeneous HPC platforms.

\vspace{-0.15in}
\begin{figure}[ht]

    \hspace{0.2in}
    \begin{minipage}[b]{0.35\linewidth}
    \centering
    \includegraphics[height=1.5in, width=1.5in]{diel-org.png}

    \caption{OpenDIEL Structure.}
    \label{fig:minipage1}
    \end{minipage}
    \quad
    \begin{minipage}[b]{0.45\linewidth}
    \centering
    \includegraphics[height=1.5in, width=2.6in]{Workflow-MC.png}

    \caption{Workflow in Materials Sciences.}
    \label{fig:minipage2}
    \end{minipage}
    \end{figure}
\vspace{-0.1in}

OpenDIEL
specifically focuses on unifying modules into a single executable
that uses MPI for communication.
Climate and materials sciences simulations, with typical workflow shown in Figure~\ref{fig:minipage2}, are two of the applications that are incorporating deep learning into their simulations.

\section{Algorithmic Improvements for DNN AI in HPC}
In this section, we select and highlight the development of two technologies that we believe are critical for the scalability and efficient use of HPC systems. The first (Section~\ref{sec:asgd}) addresses scalability of DL training, stressing the benefits and need for asynchronous methods on today's highly parallel and heterogeneous systems, featuring
powerful nodes and relatively slow interconnects. The second (Section~\ref{sec:mixed}) addresses hardware changes motivated by DL---in particular powerful hardware acceleration for low-precision arithmetic---and techniques for harnessing this in scientific HPC applications.

\subsection{Asynchronous Methods}\label{sec:asgd}

In a multi-core or many-core shared-memory environment, the speed at which
the parameters can be updated by different threads may be a limiting
factor for stochastic gradient descent (SGD) performance.  This is because threads must lock the
parameter vector while they are updating it, preventing other threads from
reading or updating the parameters, so that they must wait.  Asynchronous
versions of SGD may relax the data dependencies and order of operations
compared to the classical SGD algorithm, allowing the algorithm to update parameters
more rapidly---but also making the asynchronous algorithm mathematically different
and non-deterministic in its execution \cite{hogwild:11}.

In a distributed-memory environment, a common implementation option for
SGD is for each compute node to store a copy of the model parameters
\cite{horovod}.  When each compute node has computed a gradient for its
mini batch of data, all the gradients must be summed and then shared
among the compute nodes so that they can update their copies of the
model parameters.  This leads to a potential bottleneck in the global
all-reduce computation at every step of SGD.  In addition, nodes that
compute their gradients faster than others must wait for the other
nodes (sometimes called ``stragglers'').  This can be a very
high synchronization overhead that may be difficult to reduce by
load balancing on heterogeneous architectures.  An asynchronous
approach can address these high overheads, as we demonstrate below.

Another common implementation option for distributed-memory computers
is the parameter server approach \cite{distbelief:12}.
Here, one or more compute nodes are dedicated
to storing and updating the model parameters.  The worker nodes compute
gradients for their partition of the data and send these gradients
to the parameter server.  The parameter server then sends back the updated
values of the model parameters.  The parameter server model can be
used to run SGD synchronously---with the same issues of stragglers
slowing down the iteration for all nodes---but it has the advantage that it
can also be run asynchronously (i.e., the worker nodes do not have
to send gradients at the same time).  Workers, however, may be working
with different sets of values for the parameters at any instant.
This makes the computation asynchronous.
In distributed memory implementations, the gradients are
typically updated by the parameter
server using atomic memory operations, which differs from the shared memory case.

Asynchronous parameter server implementations were proposed around 2012 or
earlier, but it was Hogwild! \cite{hogwild:11}, with inconsistent reads and writes of
the parameter vector in shared memory, that popularized the asynchronous
approach.  In particular, Hogwild! showed that, at least in cases of convex
problems and gradient sparsity, asynchrony with inconsistent reads and writes
does not have to harm convergence asymptotically.  Hogwild! was extended
in many directions, such as
HogBatch \cite{hogbatch}, designed for efficiently running on multi-core CPU architectures,
and Buckwild~\cite{s.z.o.r:15} which exploits low-precision arithmetic
to accelerate the training. Improvements on the analysis of Hogwild! showed
that convergence can be maintained for the non-convex
and non-sparse case~\cite{NIPS2015_5751}.
In MagmaDNN, we designed a parallel asynchronous variant of SGD that is similar
to a parameter server approach, but on multi-core
CPU and GPU architectures~\cite{l.c.t.d:20}.

In practice, the accuracy of machine learning models can be dramatically
improved by increasing the number of model parameters as well as the
sizes of the training sets. As a result, the memory footprint needed
for model training often exceeds the memory storage available on a
single node. In such cases, models must be trained on large-scale
machines where the dataset, and possibly the model as well, are
distributed among the compute nodes. From a performance perspective,
it is crucial to efficiently parallelize the training in this setup---and this means overcoming the communication costs. It has been shown
that when targeting large-scale platforms, asynchronous algorithms can
outperform the synchronous ones as in the shared-memory case. In
Google's DistBelief framework~\cite{distbelief:12}, for example, the
Downpour SGD algorithm uses a centralized parameter server for storing
the model, and distributes the dataset to other participating
nodes. Asynchrony enables communications to overlap with computations,
thus improving resource usage. In addition, the algorithm is
particularly well adapted to heterogeneous computing environments
where resources may have different processing and communication
speeds.

In MagmaDNN, we take a different approach,
exploiting remote memory access (RMA) using MPI one-sided
communication capabilities for implementing asynchronous SGD in order
to maximize the scalability of parallel training. This approach has
already been proven efficient in implementing several asynchronous
numerical algorithms such as the Jacobi~\cite{jacobi-async:19} or
optimized Schwarz~\cite{optimized-schartz:19} methods for solving
sparse systems of linear equations.

\subsection{Reduced and Mixed Precision}\label{sec:mixed}

Deep neural networks can be efficiently trained using low-precision floating-point arithmetic, such as single (fp32) or lower precision, improving the training times on modern hardware~\cite{lowprec-training:14}. Popular floating-point formats include the 16-bit IEEE half-precision format (fp16) and the 16-bit bfloat16~\cite{inte18} format. With fewer bits in the mantissa compared to fp16, the bfloat16 format offers less precision but has the advantage of having the same range as fp32---thereby removing the risk of overflow and underflow when converting from fp32 data.

Motivated by the success of low-precision arithmetic in machine learning applications, many specialized hardware accelerators have been designed with reduced- or mixed-precision arithmetic capabilities. For example, the NVIDIA Tensor Cores introduced in the Volta GPU can issue $4 \times 4$
matrix multiplication $D = C + A * B$ in one clock cycle, where the input matrices
$A$ and $B$ are fp16, whereas $D$ and $C$ can be either fp16 or fp32. The theoretical performance peak on Volta GPU is 125 teraFLOP/s, which is 8 times the performance peak
for fp32; and, although the accuracy of tensor core operations is lower than fp32, the ability to accumulate the result of matrix multiplication in fp32 rather than fp16 yields a considerable gain with respect to accuracy over fp16~\cite{blockfma:20}. In~\cite{Azzam_FP16}, authors use Tensor Cores for computing a reduced-precision LU factorization of a dense linear system, initially generated in double precision (fp64), and use these factors as a preconditioner for a Krylov solver in order to retrieve an fp64 solution. By doing this, they manage to reduce the time to solution up to $4 \times$ fp64 arithmetic for the factorization.

Tensor Cores can also be used in performing FFTs~\cite{Kwai_FFT}.
Note that a matrix in fp32 can be well approximated as the scaled sum of two fp16 matrices
\begin{equation}
A_{32} \approx a1_{32} * A1_{16} + a2_{32} * A2_{16}
\label{eqn:fp32_fp16}
\end{equation}
where $a1_{32}$ and $a2_{32}$ are in fp32.
Scaling by $a1_{32} (a2_{32})$ ensures $A1_{16}  (A2_{16})$ is within the
limited dynamic range of fp16.
Conceptually, $A1_{16}$ roughly captures the 3 most significant decimal digits, and $A2_{16}$ the
next 3 lower significant decimal digits.
If $A_{32}$ is already well scaled, then one can expect $a1_{32} = 1$ and $a2_{32}=2^{-11} * a1_{32}$.
Matrix multiplication of two fp32 matrices can be approximated by 3 matrix multiplications of
fp16 matrices on Tensor Cores, which may give a theoretical speedup of 8/3$\times$ on Volta GPU.
For another perspective, equation (\ref{eqn:fp32_fp16}) suggests the form of operations in DNN are theoretically able to well approximate operations of fp32 using mixed-precision operations in fp16.

\section{Applications}

\subsection{Materials Science and Microscopy}
There are multiple opportunities to exploit machine learning techniques in materials science.
While many applications have concentrated on materials discovery---as exemplified by the use of ML in conjunction with databases such as The Materials Project \cite{Persson2013}, AFLOW \cite{Curtarolo2018}, or OQMD \cite{Wolverton2015}---a tightly coupled integration of traditional simulation techniques has great promise for  bridging the accuracy and computational cost divide between first principles calculations and effective models.
One promising combination for a tight coupling is for first principles statistical mechanics of materials to calculate the temperature dependence of materials. This requires the calculations of many possible atomic configurations within these materials using a Monte Carlo approach, where the probability of the individual states would be evaluated using an expensive density functional theory calculation~\cite{Eisenbach2009}. Thus, we will utilize ML to construct surrogate models as an intermediate step to link the first principles calculations to the Monte Carlo simulation.
Here, the calculation of ordering phase transitions in alloys might serve as an example \cite{Eisenbach2019}. In a solid solution alloy, different chemical species can occupy the sites of an underlying lattice structure (note that the total number of states grows exponentially with the number of atoms in the system). Each of these possible configurations has a different energy that determines the probability of the system being found in this state at a given temperature. To build a model for these interactions, density functional calculations for representative configurations O(1,000--10,000) will be performed to train a surrogate model that can replace the expensive (in the order of multiple node hours per data point) first principles calculation within the Monte Carlo sampling of possible configurations. While this approach can be conducted in a linear workflow, $\textrm{DFT}\rightarrow\textrm{ML}\rightarrow\textrm{MC}$, we envision a tighter coupled workflow, which augments the original training set with new points from important regions of the phase space discovered during the MC simulation, and retrains the model to improve the quantitative predictive power of this approach.

A long-standing inverse problem in atomic imaging is the loss of phase information during measurement (a.k.a., the phase problem). Given the sparse data collection of scanning transmission electron microscopic (STEM) images on different types of materials, a comprehensive database is needed for the community to study the subject. State-of-the-art electron microscopes produce focused electron beams with atomic dimensions and capture of convergent beam electron diffraction (CBED) patterns. In this dataset \cite{stemdldata}, we use newly developed electron scattering simulation codes to generate CBED patterns from over 60,000 materials (solid-state materials) from a material project database, representing nearly every known crystal structure. A data sample from this data set is given by a 3D array formed by stacking 3 CBED patterns simulated from the same material at 3 distinct material projections (i.e., crystallographic orientations). Associated with each data sample in the data set is a host of material attributes or properties which are, in principle, retrievable via analysis of this CBED stack. These consists of the crystal space group to which the material belongs, atomic lattice constants and angles, and chemical composition, to name but a few. Of note is the crystal space group attribute (or label).

This dataset could be augmented with experimental data in the future. The generated dataset, based on simulations, will emphasize the scalability aspect of the model with the use of very large images ($\sim$ 10GB per image).

\subsection{Super-Resolution for HPC Simulations}
Image compression is a very active field of study, with new methods being constantly generated \cite{sayood2017introduction}.  The need for improvements in image compression quality is growing in the field of HPC simulations because of the exponential trend in data generation.  There exists an untapped potential in this situation due to the nature of simulated data that is not currently exploited.  Simulation data from numerical systems of partial differential equations exist on a solution manifold~\cite{sol_man}.  Thus, the manifold hypothesis in machine learning---which states that real-world, high-dimensional data lie on low-dimensional manifolds embedded within the high-dimensional space---is concrete for simulation data.  We can therefore expect that identifying this map to the low-dimensional manifold will provide ideal compression for HPC Simulations. In the next paragraph we describe the basic setup that allows researchers to test in situ machine learning for climate simulations.
\par
The shallow water equations on a sphere is a well-known model used in climate science to simulate basic dynamics of the Earth's atmosphere.  There exist many test case scenarios for this model \cite{SW_Test,NJ08,OldMcDonald,GSP04}, and in this paper we use the challenging test known as the barotropic instability test \cite{GSP04}, which involves perturbing the atmospheric flow with a localized bump to the balanced height field. We simulate the shallow water equations on the sphere by using a fourth-order Runge-Kutta method \cite{RK}  for time-stepping and a discontinuous Galerkin (DG) spatial discretization with a Legendre basis on a cubed-sphere mesh \cite{CubeSphere,DG_CS_Trans2}.
\par
The data structure for this simulation consists of a time series of images for each of the six faces of the cube, which for analysis can be converted to a single series lat-lon gridded images. Arguably, the most commonly used form of lossy compression is the discrete cosine transform (DCT) method \cite{1672377}.
ECP has two projects on the development of FFTs and related transformations, one of which is heFFTe~\cite{heffte0.2}, already integrated in the ECP software stack, delivering high-performance (close to 90\% of the theoretical roofline peak), and very good weak and strong scaling on systems like Summit at ORNL.
This common compression method fills out the setup of the in situ machine learning super resolution method.  At each time step of the barotropic instability simulation, in situ machine learning methods are exposed to both the compressed image data and the original image.  As the simulation progresses, only the compressed image data is stored to disk, and the machine learning method adaptively learns correct super-resolution transformation of the compressed data. Final stored data contain all compressed image data with the trained machine learning method.  It has been demonstrated in \cite{9006550} that, using this setup, it is possible to train in situ networks to reduce the error in lossy compression---obtaining multiple orders of improvement.  Going forward, it will be necessary to further improve in situ compression and analysis in order to maximize discovery with HPC simulations.

\section{Meeting Exascale}

Exascale systems will appear in 2021. These machines incorporate accelerators from NVIDIA, AMD, and Intel. Efforts in preparing the software stack for exascale systems have been a major focus in the DOE ECP program~\cite{ECPSite}. We believe a native DNN framework such as MagmaDNN will pave a unique path to meet the challenges of exascale platforms. Assisted by the openDIEL parallel workflow engine, which admits a diverse spectrum of applications as functional modules, we will be able to exploit the full capabilities of exascale machines.  In-situ data augmentation will be incorporated with compute-intensive simulations, leading to discovery in multi- and inter-disciplinary, systems-wide, real-time recommendation systems. From instrumentation calibration, experimental and observable results, theoretical simulations, to validation and analysis---exascale computing will be brought to bear on health, transportation, environment, and social sciences. For example, climate and weather recommendation systems will be able to integrate models in storms prediction, rainfall, vegetation, farm growth, pollution, power usage, traffic flow, etc. \cite{storm,precipatation,yield,pollution,power}.
As inputs and outputs from many sensor devices become ubiquitous, the importance of a scalable AI framework and an extensible workflow tool will grow.

Challenges will rise from algorithmic approaches as HPC systems continue to expand and evolve. Multiple-precision implementation will be unavoidable. Setting the basis and preparing for product diversity from different vendors will be an important consideration of an AI framework, as well.
One challenge in performance is to reduce the
impact of communication while maintaining good convergence of the algorithm, such as SGD, in the DNN framework. In the Horovod
framework~\cite{horovod}, for example, the solution is to distribute the
training of neural network on large machines using an efficient gradient
reduction strategy referred to as ring-allreduce. Notably, in the 2018 Gordon-Bell award winning
paper~\cite{exascale-dnn-climate:18}, Horovod was used in the context
of TensorFlow to train two DNN models on large systems, including the
Summit machine, to detect extreme weather patterns from climate
data. Similarly, Horovod was used in~\cite{laanait2019exascale} to
train a large DNN model for tackling inverse
problems in imaging. Algorithmic improvements towards individual or combined synchronous, asynchronous, and pipeline approaches are essential to improve resource usage as well as convergence.

There is a trend in increasingly larg model sizes (especially in NLP---the latest model \cite{t-nlg} has 17 Billion parameters), and a need in scientific applications (e.g., geospatial imaging) to process larger-dimension inputs. Although there exist exascale deep learning applications \cite{exascale-dnn-climate:18, stemdl} on pre-exascale system such as Summit thanks to the Tensor Core technology, those use cases push the limit on large-batch training for data parallelism and are not generally applicable to exascale learning challenges. Early efforts \cite{mesh-tf, gpipe} on model parallelism have made progress, but are not yet mature or generic. An AI framework that can efficiently exploit various level of parallelisms (data parallel, model parallel, hyperparameter search, etc) will be in demand.

\section{Conclusion}
Exascale systems are an important investment in the US. With exascale, we envision a stronger economy and improved quality of life. It will also lead to important scientific discovery and resolution of complex issues related to national security. Development in AI software and tools that scale well on these systems is important, and even more critical for AI frameworks that also work well across the existing spectrum of exascale applications. Although many challenges exist, a primary roadblock is the lack of direct collaborative effort, and a software platform that values performance as the foremost priority. In this paper, we present a unique set of AI tools and algorithms, as well as efforts between collegiate and ORNL researchers, demonstrating that there is a pathway to integrate and deploy machine learning to those ends---with emphasis on two major applications on exascale systems.

\section{Acknowledgments}
This material is based upon work supported in part by the Laboratory Directed Research and Development program at the Oak Ridge National Laboratory, which is operated by UT-Battelle, LLC., for the U.S. Department of Energy under Contract DE-AC05-00OR22725. The work was partly supported by the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research, with specific thanks to the FASTMath Institutes.

This work was conducted at the Joint Institute for Computational Sciences (JICS) and the Innovative Computing Laboratory (ICL), sponsored by the National Science Foundation (NSF), through NSF REU Award \#1659502 and NSF Award \#1709069. This work used hardware donations from NVIDIA as well as the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF grant number ACI-1548562. Computational Resources are available through a XSEDE education allocation award TG-ASC170031.

\bibliographystyle{ieeetr}

\subsection{Reduced Precision}
Training deep neural networks commonly does not require high precision arithmetic where FP32 or lower precision can significant improve performance to reducing time for training without sacrificing accuracy.
There are several formats for reduced precision. One is 16-bit FP16 with 11 bits of accuracy but limited dynamic range, another is 16-bit Bfloat16 with 8 bits of accuracy but same dynamic range as FP32, and TF32  that has same dynamic range as FP32 but with 11 bits of accuracy.
Special hardware accelerators can take advantage of reduced or mixed precision arithmetic. For example, the Tensor Core on  NVIDIA Volta GPU accelerates $4 \times 4$
matrix multiplication $D_{32} = C_{32} + A_{16} * B_{16}$, where
$A_{16}$ and $B_{16}$ are $4 \times 4$ matrices are in FP16 with 11 bits of accuracy.
The peak performance on Volta GPU is 125 TFLOPS, which is 8 times the peak performance
for FP32.
There is much interest in exploiting reduced precision arithmetic on the Tensor Core.
Using LU factorization performed in reduced precision as a preconditioner of Krylov iterative method can
accelerate the solution of a large dense linear system of equations~\cite{Azzam_FP16}.
Tensor Core can also be used in performing FFT~\cite{Kwai_FFT}.
Note that a matrix in FP32 can be well approximated as the scaled sum of two FP16 matrices
\begin{equation}
A_{32} \approx a1_{32} * A1_{16} + a2_{32} * A2_{16}
\label{eqn:fp32_fp16}
\end{equation}
where $a1_{32}$, $a2_{32}$ are in FP32.
The scaling by $a1_{32} (a2_{32})$ ensures $A1_{16}  (A2_{16})$ is within the
limited dynamic range of FP16.
Conceptually, $A1_{16}$ roughly captures the 3 most significant decimal digits, and $A2_{16}$ the
next 3 lower significant decimal digits.
If $A_{32}$ is already well-scale, then one can expect $a1_{32} = 1$ and $a2_{32}=2^{-11} * a1_{32}$.
Matrix multiplication of two FP32 matrices can be approximated by 3 matrix multiplications of
FP16 matrices on Tensor Core (Appendix A), which may give a theoretical speedup of 8/3 times on Volta GPU.
For another perspective, the  equation (\ref{eqn:fp32_fp16}) suggests the form of operations in deep
neural network are theoretically able to well approximate operations of FP32 using careful use of mixed precision operations in FP16.

redpajama_set_name: RedPajamaArXiv


text:
Andy Warhol: 20 Under 20
Shapero Modern, was founded in 2014 under the guidance of Gallery Director Tabitha Philpott-Kent, and specialises in Post War & Contemporary prints, multiples and works on paper, with a particular focus on American 20th-century art.
The gallery runs a programme of exhibitions from both primary and secondary market artists, with six exhibitions per year, including collaborations with contemporary living artists as well as masters of 20th-century post war prints and works on paper.
Shapero Modern exhibits at major international Art Fairs worldwide, including TEFAF Maastricht & TEFAF New York, Frieze Masters, Masterpiece London, Art Miami, the IFPDA Fine Art Print Fair and the London Original Print Fair at the Royal Academy. Meantime, Tabitha and her team are on hand at Shapero Modern's Mayfair gallery in the heart of London to advise on all aspects of the art market and collecting.
https://shaperomodern.com
Shapero ModernLondon West End
24 Nov 2022 - 8 Feb 2023
41-43 Maddox Street, W1S 2PD
Mon-Fri 10am-6pm, Sat 11am-5pm
Forthcoming Exhibitions
9 Feb - 25 Mar 2023
W1S 2PD
London , UK
Open: Mon-Fri 10am-6pm, Sat 11am-5pm
41-43 Maddox Street, W1S 2PD, London, UK
Frieze Masters 2021
TEFAF Maastricht 2020
the GalleriesNow archive of over 10,000 exhibitions is currently only available to the GalleriesNow membership programme - click here to enquire

redpajama_set_name: RedPajamaCommonCrawl


Fandango, the ultimate digital network for all things movies, surveyed more than 8,000 moviegoers about the films, stars and characters they are most looking forward to seeing on the big screen in the new year. As part of its annual online survey, Fandango polled moviegoers from December 18 through December 26, 2017 on their top film picks for 2018. The final results are listed below, with Marvel Studios landing the top two spots, with Avengers: Infinity War named the most anticipated movie of 2018, just days after it won the same title from IMDB users, with Marvel's Black Panther coming in second place. Here's what Fandango Managing Editor Erik Davis had to say in a statement.
"The new year promises a lot of excitement at the multiplex, but fans are particularly looking forward to Marvel's Avengers: Infinity War and Black Panther, which boasts a groundbreaking ensemble and promises to be one of the most talked-about movies of 2018. These two films ruled our survey results, with Panther cast members Chadwick Boseman, Michael B. Jordan, Danai Gurira, and Winston Duke figuring prominently in each survey category. 2018 looks to offer fresh takes, new and diverse voices, and beloved characters fans can't wait to see back on the big screen again."
Rounding out the top 10 for the most anticipated movies of the year are Jurassic World: Fallen Kingdom (June 22) in third place, followed by Deadpool 2 (June 1) in fourth place and the controversial Solo: A Star Wars Story (May 25) rounding out the top 5. Many are still wondering if Solo: A Star Wars Story will be pushed from its May 25 date to a December 2018 date, since Han Solo production wrapped just a few months ago, following extensive reshoots by new director Ron Howard, who was brought in to replace fired directors Phil Lord and Chris Miller. The top 10 is rounded out by Incredibles 2 (June 15), Fantastic Beasts: The Crimes of Grindelwald (November 16), A Wrinkle in Time (March 9), X-Men: Dark Phoenix (November 2) and Ocean's 8 (June 8).
Fandango users were also polled on a number of other topics, including "Fan Favorite Actress," with Scarlett Johansson topping this poll, with two major movies coming out this year, Marvel's Avengers: Infinity War and the Fox Searchlight animated feature Isle of Dogs from director Wes Anderson. Scarlett Johansson is followed by X-Men: Dark Phoenix and Red Sparrow star Jennifer Lawrence, Avengers: Infinity War star Zoe Saldana, Ocean's 8 star Sandra Bullock and Solo: A Star Wars Story star Emilia Clarke. On the Fan Favorite Actor side, Chris Pratt took the top spot for his roles in Avengers: Infinity War and Jurassic World: Fallen Kingdom, followed by Deadpool 2 star Ryan Reynolds, Avengers: Infinity War stars Robert Downey Jr. and Chris Evans and Skyscraper and Rampage star Dwayne Johnson.
Black Panther star Danai Gurira topped the Rising Female Movie Star list, ahead of A Wrinkle in Time star Storm Reid, Deadpool 2 star Zazie Beetz, Thoroughbreds and Ready Player One star Olivia Cooke and Mary Poppins Returns star Pixie Davies. The Rising Male Movie Star poll was topped by Solo: A Star Wars Story star Alden Ehrenreich, Black Panther and Avengers: Infinity War star Winston Duke, Ready Player One and X-Men: Dark Phoenix star Tye Sheridan, A Wrinkle In Time star Levi Miller and The New Mutants star Charlie Heaton. The Most Anticipated Comic Book Character in a Standalone Movie poll was topped by Black Panther star Chadwick Boseman, followed by Aquaman star Jason Momoa, Venom star Tom Hardy, X-Men: Dark Phoenix star Sophie Turner and Ant-Man and the Wasp star Evangeline Lilly. Josh Brolin topped the Most Anticipated Movie Villain poll for Avengers: Infinity War, followed by Johnny Depp for Fantastic Beasts: The Crimes of Grindelwald, Michael B. Jordan for Black Panther, Jessica Chastain for X-Men: Dark Phoenix and Nick Castle for Halloween.
The Fandango moviegoers were also asked what their Most Anticipated Horror Thriller was, with the Untitled Cloverfield Movie coming out on top, followed by the Halloween reboot, The Purge: The Island, Insidious: The Last Key and A Quiet Place. The final poll was for Most Anticipated Family Movie, which was won by Incredibles 2, followed by A Wrinkle in Time, Mary Poppins Returns, Ralph Breaks the Internet: Wreck-It Ralph 2 and Hotel Transylvania 3: Summer Vacation. We'll have to wait and see if these Fandango users have been able to pick the biggest hits of the year in 2018.


text:
Alabama Economic News
Alabama Education News
Alabama Election News
Alabama Healthcare News
Alabama Legislation News
Alabama Local News
Alabama Opinion Editorials
Elections & Results
2022 Alabama Elections & Results
State Senators
2021 Alabama Senate Bills
2021 Alabama House Bills
Alabama Counties
Alabama Cities & Towns
Alabama Districts
Bama Politics
Dustin Chandler: If Alabama's Medical Marijuana Bill Fails, Carly's Law Will Go Away
Written by Brent Wilson on May 20, 2019
Dustin Chandler on the Matt & Aunie show. Skip to 8:00 for Medical Marijuana discussion.
Dustin Chandler appeared on the Matt & Aunie Show today to discuss the Medical Marijuana bill which he fears may be in danger of not getting a vote in the House.
If you don't know who Dustin Chandler is, he is the father of Carly, which Carly's Law is named after. Carly's law allows for CBD based oil to be used to treat severe seizures, which his daughter suffered from. He also is a very strong advocate of the CARE Act, which would bring medical marijuana to the state.
The conversation starts off talking about how Paul Lee (R-Dothan) may be intentionally stalling the bill in Committee and then goes on to talk about the bill itself.
"This is something if you read the bill, it is so well written, in my opinion, that it is a no brainer", Chandler said.
"I do know this, that Mac McCutcheon has been a supporter. I think Speaker McCutcheon needs to know there is a lot of support out in the public."
The interview soon takes a more personal turn when the discussion turns to why the bill is being stalled.
"We're not talking about, oh, this is your typical medical marijuana bill and here we go and the opposition likes to say we are just going to recreational next," he said. "That's not true. There is no basis for that statement. That is playing on fear and ignorance, which they have always done in this state."
A bit later he further expands on his fear and ignorance statement.
"We can do so much with this bill with the Universities in Alabama, every one of them has a stake in this, however, we want to go and play the fear and ignorance card and discount all of that.
Chandler goes on to say that if the CARE Act fails then Carly's Law will "go away". Carly's Law is up for renewal and the renewal of the law is tied into the CARE Act.
Chandler says that he is going to talk to as many lawmakers as he can and let them know that if the bill dies people will be hurt and that will be on their hands.
If you are interested in following updates on the bill, Carly's Law Facebook page is actively updating its followers. Please take some time to listen to the full interview which can be found embedded above or here at 8:00 minutes.
Brent Wilson
Brent Wilson was born and raised in Huntsville, Alabama and is the Owner and Chief Editor of BamaPolitics.com.
2019 Alabama Legislative Session
Alabama Healthcare
Andrea Lindenberg
CARE Act
Carly's Law
Dustin Chandler
Mac McCutcheon
Paul W. Lee
SB 236 (2019)
ReCAPTCHA Privacy Policy
© 2020 Copyright: Bama Politics


1 General Knowledge Module Overview: Fundamentally, we expect that Paddlesports Safety Facilitators (PSF) should have the ability to manage groups, have background knowledge of paddling safety and environmental hazards, and the ability to effectively maneuver their craft in order to perform and demonstrate competent rescue techniques. This certification allows the facilitator to introduce paddlecraft safety and knowledge to the beginner paddler in a land-based setting. Facilitators are encouraged to report all Paddlesports Safety classes taught while certified. This is a 1 year, non-renewable certification. Essential Eligibility Criteria (EEC): ACA courses are open to all individuals who acknowledge the ability to perform the following essential eligibility criteria. 1. Breathe independently (i.e., not require medical devices to sustain breathing) 2. Independently maintain sealed airway passages while under water 3. Independently hold head upright without neck / head support 4. Manage personal care independently or with assistance of a companion 5. Manage personal mobility independently or with a reasonable amount of assistance 6. Follow instructions and effectively communicate independently or with assistance of a companion 7. Independently turn from face-down to face-up and remain floating face up while wearing a properly fitted life jacket* 8. Get on / off or in / out of a paddlecraft independently or with a reasonable amount of assistance* 9. Independently get out and from under a capsized paddlecraft* 10. Remount or reenter the paddlecraft following deep water capsize independently or with a reasonable amount of assistance* 11. Maintain a safe body position while attempting skills, activities and rescues listed in the appropriate Course Outline, and have the ability to recognize and identify to others when such efforts would be unsafe given your personal situation* * To participate in adaptive programs, participants must acknowledge only the first six EEC listed above. Entry-level adaptive programs will involve teaching and practicing EEC # Course Prerequisites: none General Knowledge Module Duration: 4 hour minimum Discipline Specific Module Durations: 1 hour minimum, each module Instructor: This course may be offered by currently certified ACA Level 3 or higher Instructors. Additionally, this course may be offered by currently certified ACA Level 1 and 2 instructors with a Paddlesports Safety Facilitator Endorsement. If the ACA Instructor would like to offer the PSF course in another discipline (other than which they are currently certified), they must have, at minimum, an ACA Level 1 Assessment in that additional discipline to offer that module.
3 6-P s of prevention concept: Proper Prior Planning Prevents Poor Performance Universal signals: paddle, hand, whistle Weather conditions important to the Paddler: 4-W s (Water, Wind, Waves and Weather) Lightning/Storm awareness and protocols Cold shock, hypothermia and hyperthermia; prevention and treatment Signaling devices and safety equipment Boat traffic awareness and safe practice 4) Demonstrate the knowledge of the following concepts and skills: Environmental Issues: Leave No Trace Personal Preparation: planning, clothing, food and water Group Organization & Travel Trip Planning: familiar with how to prepare for a short day trip Federal, State and Local Laws and Regulations Car Topping: Loading/Unloading (use of straps and knots) 5) Demonstrate a knowledge and the ability to perform the following skills related to facilitating a group on a sheltered lake near shore: Planning a trip On-Water Etiquette Group (3 boat minimum) Group Management (Lead /Sweep, Safety, Spacing) 6) Demonstrate knowledge of and the ability to perform the following land-based rescue concepts and techniques: Possible Hazards: Submerged objects (pilings, rocks, strainers), Current, Changing water levels, other water craft Rescue Sequence (RETHROG) Rescue Priorities (People, craft, gear) Responsibilities of the rescuer, group, victim Evaluate water confidence and comfort Effective Rescue Techniques (Throw bags or Type IV flotation) to target at 30 feet 7) Satisfactorily pass the Paddlesports Safety Facilitator Exam. 8) Satisfactorily complete 1 or more discipline (craft) specific modules.


text:
Japan, AfDB Announce Up To $5 Billion In Support For Africa's Private Sector
African Development Bank Group President, Dr. Akinwumi Adesina and JICA President, Dr. Akihiko TANAKA
The Government of Japan and the African Development Bank (AfDB) have announced a $5 billion financial cooperation under the fifth phase of the Enhanced Private Sector Assistance for Africa initiative (EPSA) from 2023 to 2025.
The announcement was made at the Eighth Tokyo International Conference on African Development (TICAD8) held Sunday, August 28, 2022 in the Tunisian capital, Tunis.
The funds consist of $4 billion under the existing window, and an additional up to $1 billion that will be provided under a new Special Window. Japan will establish this Special Window to support countries that are making progress in the enhancement of debt transparency and sustainability, and other reforms, thereby making steady and significant improvement in their debt situations.
U.S Forces Kill Senior Islamic State Official In Somalia
AfDB To Commit $10 billion For The Next 5 Years To Erode Hunger In Africa
Given the importance of food security, Japan and the African Development Bank will add agriculture and nutrition as a priority area under EPSA 5. As a result, EPSA 5 will cover electricity, connectivity, health, agriculture and nutrition as priority areas in order to address key challenges in Africa.
At the EPSA 5 launch ceremony, Japan's Vice-Minister of Finance for International Affairs, Mr. Masato Kanda, said his country is committed to supporting African countries while respecting their own initiatives.
The President of Japan International Cooperation Agency (JICA), Dr. Akihiko TANAKA, highlighted the major areas of concern for Japan in Africa's multiple crisis situation.
"Under the severe situation caused by multiple crises, enhancing resilience and promoting human security are critical components of Japan's support for Africa. EPSA is an essential element of our partnership with the African Development Bank to tackle social and economic challenges facing the continent. JICA commits to work with EPSA to create a bright and prosperous future".
Dr. Akihiko TANAKA
EPSA 5 to impact millions positively
The African Development Bank Group President, Dr. Akinwumi Adesina, also underscored that the EPSA 5 is the kind of cooperation Africa and the world needs.
"Escalating climate change impacts, the Covid-19 pandemic, and the war in Ukraine means that we must do even more than we already have done, to mobilize the private sector and create job opportunities in Africa. The newly signed initiative will positively impact millions of lives across Africa."
Dr. Akinwumi Adesina
Japan and the African Development Bank will join forces to support countries that address enormous challenges, including food security, climate change, health, digitalization, and debt issues.
Japan announced the launch of EPSA at the G8 Gleneagles Summit in 2005. Since TICAD 6 in 2016, Japan has updated EPSA at TICAD. Currently, Japan is providing its support through EPSA4 (3.5 billion US dollars over 2020 to 2022), which was launched at TICAD7 in 2019.
The African Development Bank Group is Africa's premier development finance institution. It comprises three distinct entities: The African Development Bank (AfDB), the African Development Fund (ADF) and the Nigeria Trust Fund (NTF). On the ground in 41 African countries with an external office in Japan, the Bank contributes to the economic development and the social progress of its 54 regional member states.
READ ALSO: IMF Expresses Readiness To Help Lay The Ground For Stronger Growth In Ghana
Tags: AfDBafricaJapanJICATICAD8
Yellen Discusses Energy Transition In South Africa Visit
France Recalls Its Ambassador To Burkina Faso
IMF Director In Rwanda For Discussions On Climate Change Funding
Countdown of NASA Moon Rocket Launch Temporary On Hold as Fuel Leaks
Coming Months Will Be Challenging For Media Reporting – Dr. Opoku-Afari


text:
Today's Top Biotech Stories: MannKind, GSK, Myriad, and Alnylam
MannKind, GlaxoSmithKline, Myriad Genetics, and Alnylam Pharmaceuticals could all make waves in the biotech sector this morning.
Leo Sun
(TMFSunLion)
Apr 2, 2014 at 9:20AM
Follow @@TMFSunLion
Let's take a look a four stocks -- MannKind (NASDAQ:56400P706), GlaxoSmithKline (NYSE:GSK), Myriad Genetics (NASDAQ:MYGN), and Alnylam Pharmaceuticals (NASDAQ:ALNY) -- all of which could loom large in health care headlines this Wednesday morning.
FDA advisory panel recommends the approval of MannKind's Afrezza
MannKind has nearly doubled in pre-market trading today, after an FDA advisory panel voted to recommend its market approval for glycemic control in type 1 and 2 diabetes. The panel voted 13 to 1 in favor of the type 1 indication, and 14 to 0 in favor of the type 2 indication.
Although the FDA is not bound by the advisory panel's recommendation, it's a strong hint that it may be approved for both indications. The Prescription Drug User Fee Act (PDUFA) review date for Afrezza is on April 15, when the FDA will reach a final decision regarding the drug. Afrezza, MannKind's main drug candidate, has been rejected twice in the past.
If approved, Afrezza will be the second inhalable insulin approved after Pfizer's Exubera. Exubera, which was approved in 2006, was discontinued only a year later due to low demand. Afrezza, however, has a much smaller inhaler and uses a faster-acting mealtime insulin. Peak sales for Afrezza are difficult to estimate, since it's unclear if patients and doctors would choose to switch from injected insulin analogs like Novo Nordisk's Novolog.
GlaxoSmithKline's bad news drags down Agenus
GlaxoSmithKline has just stopped a clinical trial for a novel vaccine to fight lung cancer. The MAGE-A3 vaccine failed to benefit patients with non-small cell lung cancer (NSCLC) during its phase 3 study less than two weeks ago. Despite that setback, GSK originally planned to continue the trial by finding patients with a particular genetic profile on which the vaccine might work. GSK announced today that it could not find patients with that profile.
The immunotherapeutic also failed to help patients as a vaccine for melanoma. However, GSK is still investigating the vaccine's potential benefits in sub-populations for that indication. The therapeutic vaccine is intended to help patients who already have the disease, and attempts to prevent the return of the disease after surgery.
The drug's peak sales were only estimated at $233 million in 2018 by Citigroup analyst Andrew Baum after the melanoma trial failure. However, the news is dragging down shares of Agenus (NASDAQ:AGEN), which develops the adjuvant (booster) for the vaccine. Agenus' QS-21 Stimulon adjuvant is currently a key component in 21 vaccine candidates in clinical development, with GSK being one of its principal clients. Agenus only generated a little over $3 million in revenue last year and is dependent on programs like its QS-21 Stimulon adjuvant to generate future income -- income which depends on approval of vaccines like GSK's -- so this setback is certainly disappointing for Agenus investors.
Myriad Genetics rallies on a bullish upgrade
Meanwhile, Myriad Genetics is getting a positive lift this morning after being upgraded by analysts at Jefferies, who raised their price target from $30 to $33 on the stock. Analysts at Credit Suisse were also slightly more bullish on the stock, upgrading it from "underperform" to "neutral" with a $29 price target on the stock. Analysts at JPMorgan Chase currently have an "underweight" rating on the stock with a less optimistic $25 price target.
Myriad's most well-known products are its BRCA1 and BRCA2 diagnostic tests, which can identify genes which have been implicated in breast and ovarian cancers. Myriad has been under pressure due to the invalidation of several key patents by the U.S. Supreme Court, which has allowed competitors such as Ambry Genetics and Quest Diagnostics to produce similar tests. To decrease its dependence on its BRACAnalysis tests, which account for 69% of its top line, Myriad acquired blood test maker Crescendo Bioscience for $270 million in February.
Better Buy: GlaxoSmithKline vs. Merck
Here's Why Genetic Testing Stocks Lost as Much as 26.1% in May
Better Buy: Johnson & Johnson vs. GlaxoSmithKline
Alnylam's ALN-TTRsc gets a positive opinion in Europe
Last but not least, Alnylam, a company specializing in RNAi therapeutics, announced that the European Medicines Agency (EMA) Committee for Orphan Medicinal Products has recommended ALN-TTRsc for designation as an orphan drug for the treatment of TTR-mediated amyloidosis. Alnylam initiated a phase 2 trial for ALN-TTRsc for the indication last December.
Alnylam does not have any marketed products, but it has an extensive pipeline for RNAi treatments for amyloidosis, hemophilia, hypercholesterolemia, hyperlipidemia, and other indications. ALN-TTRsc is the company's second most advanced pipeline candidate after ALN-TTR02, another treatment for TTR-mediated amyloidosis which is currently in phase 3 trials.
Analysts expect Alnylam's TTR treatments to generate $1.3 billion to $2.6 billion in annual peak sales if approved -- which would be a huge boost for a company which only reported $47.2 million in collaborative revenues in fiscal 2013.
NYSE:GSK
NASDAQ:ALNY
Myriad Genetics
NASDAQ:MYGN
56400P706
MannKind
NASDAQ:56400P706
Agenus
NASDAQ:AGEN
3 Top Stocks With High Dividend Yields
Myriad Genetics Reduced 2019 Guidance, but Is It Really So Bad?
Today's Top Biotech Stories: MannKind, GSK, Myriad, and Alnylam @themotleyfool #stocks $GSK $ALNY $MYGN $56400P706 $AGEN Next Article


text:
Home World Middle East Bombings in Damascus Draw Condemnation
Bombings in Damascus Draw Condemnation
Mina Fabulous
Sat May 12, 2012
Two strong explosions in Syrian capital in Damascus killed and wounded dozens of people.
Reports say blasts occurred in the vicinity of what is reported to be a military intelligence building.
The Joint Special Envoy of the United Nations and the League of Arab States on the Syrian Crisis Kofi Annan today expressed condemnation "in the strongest possible terms" the attacks that took in Damascus.
"These abhorrent acts are unacceptable and the violence in Syria must stop." – Mr. Annan's spokesperson
Joint UNArab League Special Envoy on Syria, Kofi Annan (at podium), speaks to the press in Geneva, Switzerland, following his briefing to the Security Council this morning. UN Photo/Violaine Martin
Mr. Annan said he is saddened by the loss of life resulting from the two blasts and extends his condolences to the families of the victims.
The Joint Special Envoy reiterated his call to all parties to adhere to an agreed cessation of violence.
Mr. Annan said any action that serves to escalate tensions and raise the level of violence can only be counter-productive to the interests of all parties.
Annan calls on all parties to avoid further bloodshed and to protect civilians.
On Wednesday, at least six soldiers were wounded as a bomb hit UN Observer Convoy while entering the city of Dara'a.
Reports say the roadside bomb exploded after the passage of four vehicles carrying the UN team, hitting the troops traveling behind them.
UN Spokesperson Ahmad Fawzi reported that there were no casualties among the observers, but several Syrian soldiers were injured and taken to hospital.
Major General Robert Mood (centre), Chief Military Observer and Head of the UN Supervision Mission in Syria (UNSMIS), meets with members of the opposition in Al-Rastan, a town in Syria's Homs province. UN Photo
The Security Council has authorized the establishment of a United Nations observer mission to Syria, for an initial period 90 days.
In a unanimous decision, Council members passed a resolution calling for the formation of the "United Nations Supervision Mission in Syria (UNSMIS), comprising an initial deployment of up to 300 unarmed military observers as well as an appropriate civilian component."
The UNSMIS is tasked with monitoring the cessation of violence in Syria and supporting the full implementation of a six-point plan put forward by Mr. Kofi Annan.
On 27th of March 27, Mr. Annan reported that the Syrian government had accepted the six point-plan and pledged to implement it.
According to report, below is the the six-point plan which asks the Syrian authorities to:
(1) commit to work with the Envoy in an inclusive Syrian-led political process to address the legitimate aspirations and concerns of the Syrian people
(2) commit to stop the fighting and achieve urgently an effective United Nations supervised cessation of armed violence in all its forms by all parties to protect civilians
(3) ensure timely provision of humanitarian assistance to all areas affected by the fighting, and to this end, as immediate steps, to accept and implement a daily two hour humanitarian pause
(4) intensify the pace and scale of release of arbitrarily detained persons, including especially vulnerable categories of persons, and persons involved in peaceful political activities, provide without delay through appropriate channels a list of all places in which such persons are being detained
(5) ensure freedom of movement throughout the country for journalists and a non-discriminatory visa policy for them;
(6) respect freedom of association and the right to demonstrate peacefully as legally guaranteed.
The violence in Syria, which began in March 2011 as a protest movement similar to those witnessed across the Middle East and North Africa, has claimed over 9,000 lives, mostly civilians, and displaced tens of thousands.
Mina Fabulous follows the news, especially what is going on in the US State Department. Mina turns State Department waffle into plain English. Mina Fabulous is the pen name of Carmen Avalino, the NewsBlaze production editor. When she isn't preparing stories for NewsBlaze writers, she writes stories, but to separate her editing and writing identities, she uses the name given by her family and friends.
United States Abandon Kurds: How Will This Move Impact Middle East
IHMEC project indoor hygiene solutions for infection prevention and control support Saudi Vision 2030
Pakistan Embassy in Saudi Arabia Marks 73rd Independence Day in-solidarity with Kashmir
Dubai's Supercar Scrapyard: Luxury Vehicles Left in the Dust after Owners Default on Loans
The Failed OIC Summit of Mecca and Saudi Panic
Europe Month Announced by EU Ambassador to Saudi Arabia, Michele Cervone
Tourism Rebounds in Egypt: Here's Why Its A Great Location Again
Here's How Coach Meddy Is Leaving an Indelible Mark on the Fitness World
Pakistani Embassy in Saudi Arabia Celebrates Pakistan day
Middle East News from PR Newswire


text:
Sports Logo News
By TVIXX, September 15, 2016 in Sports Logo News
Matito 457
Muh-TEE-Toh
Location:St Petersburg, FL
Favourite Logos:Rays Stingray logo
5 hours ago, SilverBullet1929 said:
Every time I see it, the Marlins gray jersey gets closer and closer to becoming my favorite of theirs. It's just sharp looking. It's the right balance of them wanting to use black and wanting to be colorful because the gray is a perfect base for that. The white wordmark is a fabulous touch. You'd never think a white wordmark would work on a gray jersey but this one shows it can. Makes me wonder if any other teams could do it.
I think white can look really good on a gray uniform when used correctly, and Miami does a good job.
I forget who, but a while ago, I saw someone in the Concepts forum who had a concept for a baseball team whose main color was white, using just a dash of blue and red as accents, and it was really well done. I'd like to see someone embrace it like that.
daveindc 1,491
Why are the Mariners using the slogan True To The Blue if they use 2 shades of blue and their most recognizable color is teal? I dunno, I know it still fits but out of all teams that wouldn't have been the team that I'd expect to use that slogan. Maybe the Dodgers, Royals or even Cubs.
I think the Mariners would benefit from switching to a lighter shade of navy throughout their set. At this point all they need to do is lighten the letters and wear the lighter shade of navy cap like the Padres and Rays wear. The navy they have now to me just seems unnecessarily dark and stale. The lighter shade brightens up the overall look, with the teal continuing to pop.
Around the Horn 999
20 hours ago, Brandon9485 said:
Even though I yearn for the days when the Marlins wore teal, I really do like their current road greys. The white wordmark on a grey uniform really works for me here.
Swap out the black piping and NOB in their uniform set for their shade of light blue (or teal?) and this is one hell of a jersey...
TheOldRoman 1,271
4 hours ago, daveindc said:
1) I disagree with you. The lighter shade of navy is bad. Also, as far as I know, the teams wearing the lighter navy hats still use the same dark navy on the jerseys. If anything, they should lighten up the teal a hair.
2) This picture show how crappy the matte helmets are. They're two weeks into the season and the helmets are already scuffed up with glossy marks on them. Shiny helmets masked scuffs much better.
joey joe joe jr. shabadoo 620
On 4/15/2017 at 4:54 PM, Brandon9485 said:
Jackie Robinson deserves celebration, but I am against league wide number retirements. I wish they had left 42 alone and made every player wear it on April 15th.
The NHL should unretire 99 as well. Let Edmonton, Los Angeles, St. Louis, and the New York Rangers retire it if they want to.
No single player is bigger than the game. No numbers should be taken out of circulation in an entire league. Not Gretzky or Robinson
Plus Gretzky was more linked to his number (which was unusual at the time) while Robinson for what he endured and the courage and grace that he showed in paving the way. But 42 isn't iconic in any way outside of baseball...99 is sort of inseparable from Gretzky.
That said as a Met fan I can tell you there are still many MANY Mets fans that, while very appreciative of Robinson, feel that the entrance to their stadium should not be a shrine to Jackie Robinson & the Dodgers. That when entering the stadium...things still don't quite feel right.
SilverBullet1929 2,969
Location:Miami, Florida
Favourite Logos:Miami Marlins and too many others to name...
Are we positive the Mariners use the darker navy? I feel like I know they do but I just watched the Marlins play three games at Safeco Field, which I never do as the Marlins haven't played there since 2011... but I couldn't stop thinking how light the navy looked in every single use of it. I just kept thinking that their navy looks way more like the Rays navy than the Yankees navy... so what's the problem? I think the pics above show this too. Am I wrong? Anyone else ever noticed this?
The Golden One 135
A's President on AMA just mentioned this about next year...
" We have one throwback this year and next year to celebrate the 50th anniversary of the club in Oakland we are going to go wild with throwback nights! "
WSU151 6,283
Location:DC area
I have a hat, and it's definitely the darker navy.
Quillz 1,095
Favourite Logos:Angels, Bills, Blue Jays, Chargers, Dodgers, Kings, Lakers, Lions, Panthers, Rams, Tiger-Cats
I really hope at some point the Dodgers fix their back numbers. They are too thin! Either go back to the (standard) thicker variant (as seen on the Royals and some other teams), or go back to having a barely-visible white outline. This seriously irks me and I can't stop seeing it.
insert name 4,189
Location:In The City
More of a reason they should've kept the orange bill. The hats are too similar to each other.
Wow. Bronchitis, a sick grandfather, and a sudden trip to South Carolina really got me behind here. Time to catch up.
On 4/9/2017 at 9:55 AM, SilverBullet1929 said:
Without disagreeing with this, you're speaking from the stance of uniform and logo buffs like us. The general public doesn't care that the Marlins use too much black, the Miami Heat use black and people here love it and nobody minded the Marlins using black before this rebrand either. People also don't hate the use of orange, they just prefer teal because it's what the Marlins embraced for a time and it's the recognizable color of the team before 2012. Also the Dolphins and the Hurricanes use orange down here as well. And the team not being as colorful as they said they'd be is not why people down here don't like the look as most here were shocked that the logo was so colorful and were fearing a rainbow uniform set. While you and I would love if they went with more blue than black if you asked the general population down here in South Florida they'd be skeptical of the thought of the team using even more colors.
With that said, I believe we're giving two different sides of the same debate (uniform lovers vs South Florida sports fans)... and my only original point was that for all the shock it caused at the time of its unveiling, the Marlins rebrand is not as extreme as many made it out to be.
I wasn't arguing the idea that they seem less extreme now, especially compared to the things that have come since. I was arguing about your statement that any hatred of the rebrand came from only the logo or a nostalgia for the previous identity.
On 4/10/2017 at 11:55 AM, aawagner011 said:
What I find odd is the pattern they chose to go with. It looks like it's crocheted. What about this pattern screams "Braves"?
On 4/10/2017 at 10:04 PM, kroywen said:
I think the best "policy" for the New Era logo, if it has to exist, is for the logo to match the primary color of the monogram on the front of the cap. So, for instance, on the Cards' red caps, it'd be white (since the StL is primarily white), while on the Cards' blue caps, it'd be red. Having a New Era logo that doesn't match the primary color of the monogram is just jarring. For teams that wear logos on their caps, use the primary color of the logo.
The problem is that half of the time the outline is there to better contrast the cap. The primary color may not look right straight on the crown color. In the end, either way looks wrong for multi-color teams.
On 4/11/2017 at 0:48 PM, BJ Sands said:
Other than one or two throwback games, the Cubs haven't worn blue at home since the Ricketts family bought the team. For them to raise the banner in anything other than white uniforms with blue pinstripes would have been wrong.
For them to win the banner in a colored alternate uniform would have been wrong.
On 4/11/2017 at 1:49 PM, aawagner011 said:
They've done this for a few years now, but why do the Braves get stuck with a headspoon and sleeve trim that they don't actually wear on any of their normal uniforms? From what I can tell (unless I'm missing a team), everyone else gets treated like their normal uniforms.
I think the piping comes from the fact that the braves alt without the tomahawk only has single piping. Thus, when the template got taken to other uniforms, this piping became the norm instead of the standard piping.
Or it could just be simplification to keep the color palate small. Everyone with double/triple piping has just single now. See the Twins, Angels, Nationals, etc.
On 4/11/2017 at 4:45 PM, SilverBullet1929 said:
The HR derby caps, I love the simple black caps with orange logos, nothing wrong there. The floral pattern underbrim and socks will make me poke my eyes out with a broomstick. Chris Creamer said the pattern is very Miami Marlins. Tell me where the Marlins use this gaudy garbage on their uniforms? The Marlins imply a strong use of colors but there isn't this trash bag full of colors anywhere on them but suddenly it's on these socks and caps.
Also, one video I saw said the lightweight material is to combat the hot Miami weather, which is nice in theory but the ASG is being held in an air conditioned retractable roof ballpark so that thought goes right out the window.
I'm expecting they hope that they're going to open the roof and windows for such a big showcase of the facility, let in that Miami in July air.
On 4/11/2017 at 9:14 PM, Sec19Row53 said:
So the Brewers wear Milwaukee at home and Brewers on the road. To quote a professor of mine from long ago 'da hell?'
I wish I had that professor.
On 4/12/2017 at 7:57 AM, VDizzle12 said:
I would hope so. It's probably the best selling hat they have, which is why they tried to force it with the navy alts.
Hopefully they can add another alternate uniform next season to use it with. Maybe a red jersey or something it fits better with.
Maybe just go with the Cardinals method? Red caps on Sundays over the home whites with red accessories? I don't know about a red alt. That would necessitate a white or navy wordmark, and neither of those feel right. Maybe with a navy C on the chest, but then you look too much like the Twins' alt. Of course, I'd rather the Twins wore their Dairy Queens.
Do world series winning teams usually give rings to their tv broadcasters?
I've never heard of this practice. I don't think John and Suzyn have rings, and... I kinda feel okay with that.
On 4/12/2017 at 7:44 PM, Bucfan56 said:
So, they made 2016 World Series rings for Ron Santo and Ernie Banks? Why?
The same reason fans left jerseys on gravesites.
On 4/13/2017 at 0:20 PM, Ferdinand Cesarano said:
Anyway, we are discussing not the wordmark but only the crooked C hat, which would be appropriate with the current uniform. In 1973 the crooked C cap logo replaced the wishbone C, which was identical in shape to the Reds' logo, and which had been worn since the mid-1930s. If the crooked C had been left in place, it would today have been on the cap for longer than the wishbone C was; and absolutely no one would be characterising it as offensive in any way. Also, the Wahoo logo would never have experienced the elevation in status that it received in 1986 when it became the cap logo for the first time in team history; and that logo might conceivably have been retired by now.
I will agree that the block C is the worst cap logo in the Majors. It's barely appropriate for a beer league team; for a Major League team it's an embarassment.
For so many reasons, the crooked C is the answer.
On the subject of the old C, a lot of people take issue with the disparity of elements in that idea. The C in the old cursive wordmark was never really anything special or celebrated in the hearts of fans. I wonder how it would look if you switched them. Then you could put that on the road and the identity would be unified.
On 4/13/2017 at 1:53 PM, hjwii said:
The answer is simply a plain, blue cap. Can't offend anyone if there's nothing there. Besides, way back when the Cleveland Baseball Club (don;t want to use that "I" word) wore a plain, blue cap, so it's historically accurate.
The Browns of baseball.
On 4/14/2017 at 0:29 AM, schtee said:
I realize that Cleveland's block "C" has historical precedent from the 1910s and their 1920 World Series, but not only is it lifeless it looks too much like the "C" on Cal Berkeley's baseball caps. Slight difference in the serif on the upper right.
To me it looks more like the original White Sox logo.
On 4/14/2017 at 10:22 AM, WSU151 said:
The green walls are awesome, and a fish tank in the outfield would be incredibly similar to the Rays' tank at the Trop.
I hate those walls. Not only does the green look more like the produce section at your local grocery store or a placeholder to be green-screened in later. Meanwhile, the team's got half a dozen colors and they had to bring in a completely different color not anywhere in their pallette for the walls? Their old teal (a throwback to their original home) or their new blue would have both been so much better. I would have taken orange. Why not a traditional Caribbean pastel blue?
This is made more jarring by the old giant walls that, rather than being made of the material of other walls in the park, were made the same color as the fences, but were huge swaths with nothing breaking them up.
I'm glad the above pictures of the updated park show a much more reserved use of this green. Yes, I understand the level system the park has. The lower floor is green. But it was just too much of a bad color.
On a side note, while looking for the above picture, I found that apparently the original concepts showed a more traditional green wall color.
On 4/14/2017 at 10:21 PM, Ferdinand Cesarano said:
Very few people would contend that the Indians' name is what is offensive. (And no one in the present discussion has done so.) Despite its origin in error, the term "Indian" has become entrenched; and most Native groups refer to themselves as Indians. Even though no new team could justifiably take that name, Cleveland's use of the name is not the thing that typically comes in for criticism. The problematic part of the Indians' identity is the awful Wahoo logo.
While I do agree with you, reasoning on the names of older organizations quickly becomes a slippery slope.
(What is ironic is that the Washington Redskins, a team whose name is offensive, have a logo that is relatively benign. If the Indians had the Redskins' logo instead of Wahoo, we can imagine that the team would probably be held up as an exemplar of a dignified portrayal of Natives.)
Oh... Oh good lord. Now I'm picturing a team with the name Redskins and the Wahoo logo. The horror. The horror.
On 4/14/2017 at 10:43 PM, Solaris said:
If you have such an issue with Indians being made as a logo, why aren't the Blackhawks being given a hassle about their logo? Oh, that's because it's "dignified". If I remember correctly, the people who were protesting the home opener had signs that read, "We are not characters".
I think people need to move past this issue. What's interesting is that the fans are not being listened to, it's people who have zero interest in baseball and the Cleveland Indians who are telling the organization to change.
Again, I'm not necessarily arguing for or against Wahoo, but this argument kinda falls apart quickly. Nobody says that outsiders should have considered the feelings of those who were fans of minstrel shows before arguing they were unacceptible.
Overall, one thing I'm noticing with these looks is that a lot of these things are great in a vacuum, so basically they're perfect for fans to buy because they'll look cool when you're wearing them on the weekend just hanging out. So what they've basically made here is excellent fan fashion caps and jerseys but are forcing the players to wear them on the field where they'll actually look pretty bad overall. So it's clear to see what this is all about and I don't have to explain that to anyone here because we all know it. These are for the fans and not the players.
On 4/14/2017 at 10:58 PM, MCM0313 said:
Those would be good divorced from the tradition-rich history of baseball uniforms in general, and the Giants' uniforms in particular. I think they look pretty solid as a standalone item.
This is my constant struggle, especially being a fan of traditional looks and having a traditional team that I never want to change. I love white and gray, but dangit so many colored alts look good. Same for some of the Stance socks that shirk already established designs and traditional design, but just kinda look cool. I actually do dig the All-Star look this year.
On 4/15/2017 at 6:14 AM, Ferdinand Cesarano said:
They were thinking "these look great". And they were correct.
Well, they were correct insofar as the stirrups are concerned. Those stripes above aren't helping.
But I don't care whether the stirrups are real or fake. They look like stirrups; so they're good. Likewise, I wouldn't really mind if a pullover jersey had a false front of buttons, as long as it preserved the appropriate look.
Fake stirrups or two-in-ones are perfectly fine. Seeing them in action still fills me with the same apprehension I had when I first saw them. Those stripes across the ankle ruin any attempt to try to look like stirrups for me.
At least they're halfway decent from the side. More like stirrups with high-top shoes.
When the month is over, we should have seen all combinations and teams that aren't going to constantly switch things up anyway. I'll have to put together a report card on how everything looks.
On 4/15/2017 at 11:18 AM, Brandon9485 said:
I am not a fan of this Twins uniform. The Rangers already can't decide if they're a blue team or a red team. I think the Twins could be starting down that road.
The Red Sox, Orioles, Rays, Astros, Athletics, Mariners, Nationals, Marlins, Braves, Pirates, Giants, and Rockies all wear regular colored alts of their two primary non-white colors, and others have done it in the past. It's a common practice. Not really anything to worry about.
I know Buster Olney was championing 21 for Roberto Clemente (and I understand why), but where does it end? That's why I don't like league-wide retirements. It starts a league down a slippery slope.
Yeah. Once you introduce the possibility of there being more than one league-wide retiring, the floodgates do open, even though I think Clemente well worth it if it was. Then you'll have the arguments for 44, 3, 4, 24, 9, 34, 6, or even... *shudder* ...14.
On 4/15/2017 at 9:32 PM, Dolphins Dynasty said:
I bet in 100+ years, teams are going to start running out of available numbers.
I feel you. Our top new guy is wearing 99. We're already out of single digits.
Although we all know that a thousand years from now it's the Mets that will be in trouble. (I dig that the racing stripes will eventually come back.)
Dear Minnesota Twins,
I'll give you some credit for trying to switch things up and add gold to your uniforms. Truth is it's a disaster, and you already had a great home uniform. Time to cut your loses and revert back to this beauty full-time.
That text is so wonky. I'd rather they put pinstripes on the current navy outlined in red wordmark and modernize it. Drop the gold. It would look good and differentiate from the Homerdome style, which they can save for Friday nights or something.
On 4/17/2017 at 4:15 AM, batman1211 said:
I think a "TC" logo is fine if they want to be the Twin City Baseball Club. Right now it is just ridiculous. "Twins" is okay if you want to be the Minneapolis & St. Paul Twins. If you are Minnesota, then find a mascot that represents the whole state. I think their whole identity and logo is a hodge podge of confusion. IMO, figure who you represent then create any identity around that. Right now they don't know if they represent the state, or two cities within. I think they have the weakest identity in any major sports league.
There's three reasons for wearing a name other than your city's.
1. You're trying to obscure where you're playing/not alienate a nearby market of another name. (California Angels, Florida Panthers, Tampa Bay Rays/Lightning/Buccaneers, New England Patriots/Revolution, Carolina Panthers, Golden State Warriors,)
2. You're the first/only team in the state and want to plant your flag/show that you represent everybody. (Florida Marlins, Arizona Diamondbacks/Coyotes/Cardinals, Carolina Hurricanes, Colorado Avalanche/Rapids, Tennessee Titans. Utah Jazz)
3. Your name is an established phrase. (Texas Rangers, Colorado Rockies.)
The Twins are an example of #1, not #2. About every team before them wore the name of one of the Twin Cities and failed as they alienated the other. The Twins decided to avoid this issue, and if I recall correctly they became the first state named team in professional sports in the process. Almost all Minnesota-based teams followed suit.
On 4/17/2017 at 5:53 AM, Ray Lankford said:
The gold on the Twins' jersey is unnecessary but pretty inoffensive considering that you can barely see it from a slight distance.
I don't think I will ever get over the fact that they wear an alternate cap as their standard home cap. It just... turns a rage switch on in my brain. It feels more against any established tradition or rules than anything the Diamondbacks or Stance have trotted out.
Okay, the soapy teal almost made me rant as much, but the alternate home is still worse.
On 4/17/2017 at 0:52 AM, SFGiants58 said:
I'd mentioned above my dream vision for the Twins' identity. That being said, the color scheme of those alts are very unique and sharp. I'd love to see them on someone, although I'm not 100% sure it's the twins. Maybe the White Sox should add a splash of red.
Now for new business. Anyone else watching the games/highlights in Pittsburgh? What's with the helmet being worn by the base coach (not sure what side)? It's got really complicated vents on it that the players don't wear, and looks nothing like the old vented/two-toned helmets.
FinsUp1214 4,017
Joe InGOAT
Location:Provo, Utah
Favourite Logos:Minnesota Wild primary Montreal Expos cap San Diego Padres "Swingin' Friar" Indianapolis Colts primary Cincinnati Bengals "leaping Bengal"
On 4/20/2017 at 7:09 AM, SilverBullet1929 said:
The helmets, alt jersey, and catching gear look lighter navy, but the hat at least is definitely the dark navy. I own both a Mariners and Padres cap, and the Padres navy is the lighter of the two.
Mayor Daily 1
Sorta random, but I found this in a Puerto Rican news article about prospect Heliot Ramos, and thought it was an interesting variation on the White Sox set.
Big Yellow Flag 143
Jackie's number should be unretired by everyone but the Dodgers (you could probably make a case for the Mets, too, but I won't like it). Jackie Robinson Day should be a thing, where people where a patch on the sleeves of jerseys with their normal numbers on the back.
We're going to be coming up on a time soon when people don't remember Jackie. Old Brooklyn Dodgers faithful are dwindling. Having everyone wear his number and no name once a year will change nothing, and the memory will slowly fade away. Allowing it to be worn (which most still won't, since they're already attached to their numbers) will let kids in 30 years see it on the back of their favorite player, wonder why he's wearing it, and do some research.
Also, hope this is okay, I took the TC posted a page or two ago and did a quick mockup of the split color look they have now.
Looks amazing.
2 hours ago, Big Yellow Flag said:
Having everyone wear his number and no name once a year will change nothing, and the memory will slowly fade away. Allowing it to be worn (which most still won't, since they're already attached to their numbers) will let kids in 30 years see it on the back of their favorite player, wonder why he's wearing it, and do some research.
But if everyone is wearing #42, won't kids in 30 years wonder why this is the case, and do some research?
1 hour ago, Quillz said:
You might be right, we'll find out in thirty years.
You think we're all going to forget about Jackie Robinson once everyone who saw him play is dead?
Historical memory doesn't work like that
54 minutes ago, Big Yellow Flag said:
I'm saving this post, expect me to reply to it in 30 years.
25 minutes ago, Ice_Cap said:
Who he was won't be forgotten, but his incredible impact very well might be. The average baseball fan (I just asked my friends who are sitting near me, all casual fans) has already forgotten Branch Rickey.
But if they continue having Jackie Robinson day then his impact won't be forgotten. Branch Rickey isn't specifically remembered because they don't have Branch Rickey Day.


Estimates a collection of time-indexed functions under either of Gaussian process (GP) or intrinsic Gaussian Markov random field (iGMRF) prior formulations where a Dirichlet process mixture allows sub-groupings of the functions to share the same covariance or precision parameters. The GP and iGMRF formulations both support any number of additive covariance or precision terms, respectively, expressing either or both of multiple trend and seasonality.
Please use the canonical form https://CRAN.R-project.org/package=growfunctions to link to this page.


Maffucci's syndrome, a rare disorder that affects the skin and bones, can cause significant disturbances in your life. Characterized by benign overgrowths of cartilage in the hands and feet (enchondromas), Maffucci's syndrome causes skeletal deformities, dark red patches, and potentially malignant cell growth.
Although receiving a diagnosis of Maffucci's syndrome can be traumatic, with proper medical attention, the disorder can be managed. If you have been diagnosed with Maffuci's syndrome, enlisting the services of a skilled doctor is your first step in obtaining the treatment you need.
The exact cause of Maffucci's syndrome is not fully understood. The disorder appears to stem from improper bone and skin development in-utero or in early childhood. Genetic factors may also play a role in the development of Maffucci's syndrome. Maffucci's syndrome causes some cartilage to grow irregularly as the bone grows, eventually forming the bone deformities that characterize the syndrome.
Bone abnormalities (i.e. legs that are unequal in length, bones that fracture easily, fractures that do not heal properly).
If Maffucci's syndrome does not cause symptoms, treatment may not be necessary. However, ongoing medical evaluation is crucial in order to monitor any changes of the skin and bones. When symptoms are excessive, malignant transformations can occur in the skin and skeletal regions, at this point treatment might be necessary. The goal of treatment is to manage the symptoms and restore the bones and skin as much as possible.
If you are experiencing the symptoms of Maffucci's syndrome, or if you have been diagnosed with the disorder, contact your doctor to obtain the treatment you need. A skilled medical professional can help manage your symptoms and improve your prognosis.


"More Holiday" with the Pyhrn-Priel ActiveCard! Numerous attractions and destinations in the region can be enjoyed at no cost and as many times as you like from the middle of May to the beginning of October. About 180 hosts include the Pyhrn-Priel ActiveCard, including about 40 free and 20 discounted services, from one overnight stay onwards free of charge.


text:
Suffolk University Law School Parking
Founded in 1906, the mission of Suffolk University Law School was to provide a good legal education to those who may be thwarted from doing so otherwise, due to socio-economic or racial discrimination. As the fourth oldest New England law school in continuous existence, Suffolk University Law School still lives up to its original intention and even offers over 200 upper level electives, which is more than any law school in the US. While being consistently ranked as one of the most technologically advanced schools in America, Suffolk University Law School is highly lacking when it comes to parking. The convenient downtown location can make parking quite dubious, unless you have a good plan. No worries, SpotHero has the solution. We have numerous convenient parking options near Suffolk University Law School. You will save both time and money when using SpotHero to secure good Suffolk University Law School parking. Best of all, when you use SpotHero, your parking is always guaranteed. Search for and reserve affordable Suffolk University Law School parking with SpotHero now.
Suffolk University Law School Parking Information
120 Tremont St Boston, MA