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The Opposite of the Embarrassingly Parallel Problem

Heidi Brayer

2/9/2015 4:59:00 PM

Graph algorithms are in wide use in Department of Defense (DoD) software applications, including intelligence analysis, autonomous systems, cyber intelligence and security, and logistics optimizations. In late 2013, several luminaries from the graph analytics community released a position paper calling for an open effort, now referred to as GraphBLAS, to define a standard for graph algorithms in terms of linear algebraic operations. BLAS stands for Basic Linear Algebra Subprograms and is common library specification used in scientific computation. The authors of position paper propose extending the National Institute of Standards and Technology's Sparse Basic Linear Algebra Subprograms (spBLAS) library to perform graph computations. The position paper served as the latest catalyst for the ongoing research by the SEI's Emerging Technology Center in the field of graph algorithms and heterogeneous high-performance computing (HHPC). This blog post, the second in our series, describes our efforts to create a software library of graph algorithms for heterogeneous architectures that will be released via open source.

The Opposite of an Embarrassingly Parallel Problem

In computer science, the term embarrassingly parallel problem describes a situation where the same operation or set of operations can be executed on different data simultaneously, thereby allowing the distribution of data across many computing elements without the need for communication (and/or synchronization) between the elements. The problems are relatively easy to implement on high-performance systems and can achieve excellent computing performance. High-performance computing (HPC) is now central to the federal government and many industry projects, as evidenced by the shift from single-core and multi-core (homogenous) central processing units (CPUs) to many-core and heterogeneous systems, including graphics processing units (GPUs) that are adept at solving embarrassingly parallel problems.

To read the complete post, please visit
http://blog.sei.cmu.edu/post.cfm/developing-a-software-library-for-graph....