To implement dense linear algebra algorithms for distributed-memory computers, an expert applies knowledge of the domain, the target architecture, and how to parallelize common operations. This is often a rote process that becomes tedious for a large collection of algorithms. We have developed a way to encode this expert knowledge such that it can be applied by a system to generate mechanically the same (and sometimes better) highly-optimized code that an expert creates by hand. This paper illustrates how we have encoded a subset of this knowledge and how our system applies it and searches a space of generated implementations automatically.
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