Log(Graph): A Near-Optimal High-Performance Graph Representation (2018) [pdf]
This paper on succinct graph data structures will be presented at PACT (<a href="http:&#x2F;&#x2F;www.pactconf.org" rel="nofollow">http:&#x2F;&#x2F;www.pactconf.org</a>) next month.<p>To put it in the broader context of relational database programming and why it&#x27;s significant now for software developers in general, here are some thoughts from a thread I posted yesterday [0] on the convergence of ideas that have been in the works for the last 10+ years on the graph database front and the forces that have aligned in hardware and other fronts to bring about the architectural paradigm shift that&#x27;s to come...<p>[0] The design and implementation of modern column-oriented database systems <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=18076547" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=18076547</a><p><pre><code>   --&#x2F;&#x2F;--
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This upcoming paper [...] is more data model than database, but I think you&#x27;ll find it interesting.<p>For something more database specific, check out the new RedisGraph module [1] implemented with GraphBLAS [2] by the venerable Tim Davis [3] himself, who as you know implements the underlying sparse matrix algos used in everything from MATLAB to Google Maps...<p>RedisGraph in the Language of Linear Algebra with GraphBLAS, co-presented by RedisLabs and Tim Davis [video]<p><a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=xnez6tloNSQ" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=xnez6tloNSQ</a><p>GraphBLAS is not Redis-specific, but the Redis data structures and new modular design made it an ideal candidate for the first popular database implementation.<p>This is significant because GraphBLAS is more than 10 years in the making, the culmination of the initial D4M matrix model design by Jeremy Kepner [4] and his team at MIT Lincoln Laboratory Supercomputing Center.<p>And for the last ~5 years or so the software model has been designed in collaboration with hardware teams at Intel, NVIDIA, IBM, and the labs [5] to make chips and architectures optimized for these new matrix models and capable of exascale.<p>It all came together this summer with the release of GraphBLAS 1.0 [6]. Now that GPU and TPU accelerators are populating the data centers and linear algebra has come en vogue, hopefully enough software engineers will be ready with the background understanding and a working mental model for the underpinning architectural paradigm shift [7].<p>[1] RedisGraph <a href="https:&#x2F;&#x2F;oss.redislabs.com&#x2F;redisgraph&#x2F;" rel="nofollow">https:&#x2F;&#x2F;oss.redislabs.com&#x2F;redisgraph&#x2F;</a><p>[2] GraphBLAS <a href="http:&#x2F;&#x2F;graphblas.org" rel="nofollow">http:&#x2F;&#x2F;graphblas.org</a><p>[3] Tim Davis <a href="http:&#x2F;&#x2F;faculty.cse.tamu.edu&#x2F;davis&#x2F;" rel="nofollow">http:&#x2F;&#x2F;faculty.cse.tamu.edu&#x2F;davis&#x2F;</a><p>[4] Jeremy Kepner <a href="http:&#x2F;&#x2F;www.mit.edu&#x2F;~kepner&#x2F;" rel="nofollow">http:&#x2F;&#x2F;www.mit.edu&#x2F;~kepner&#x2F;</a><p>[5] GraphBLAS: Building Blocks For High Performance Graph Analytics <a href="https:&#x2F;&#x2F;crd.lbl.gov&#x2F;news-and-publications&#x2F;news&#x2F;2017&#x2F;graphblas-building-blocks-for-high-performance-graph-analytics&#x2F;" rel="nofollow">https:&#x2F;&#x2F;crd.lbl.gov&#x2F;news-and-publications&#x2F;news&#x2F;2017&#x2F;graphbla...</a><p>[6] Graph algorithms via SuiteSparse:GraphBLAS: triangle counting and K-truss [pdf] <a href="http:&#x2F;&#x2F;faculty.cse.tamu.edu&#x2F;davis&#x2F;GraphBLAS&#x2F;HPEC18&#x2F;Davis_HPEC18.pdf" rel="nofollow">http:&#x2F;&#x2F;faculty.cse.tamu.edu&#x2F;davis&#x2F;GraphBLAS&#x2F;HPEC18&#x2F;Davis_HPE...</a><p>[7] David Patterson Says It’s Time for New Computer Architectures and Languages <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=18009581" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=18009581</a>