Wed 17 Jun 2015 14:50 - 15:15 at PLDI Main BLUE (Portland 254-255) - Parallelism Chair(s): Sara Baghsorkhi

This paper introduces two new compiler transformations for representing and transforming sparse matrix computations and their data representations. In cooperation with run-time inspection, our compiler derives new sparse matrix representations and associated transformed code to implement a variety of representations targeting different architecture platforms. This systematic approach to combining code and data transformations on sparse computations, which extends a polyhedral transformation and code generation framework, permits the compiler to compose these transformations with other transformations to generate high-performing code that is within 5% and often exceeds manually-tuned, high-performance sparse matrix libraries CUSP and OSKI. Additionally, our compiler-generated inspector codes are on average 1.5x faster than OSKI and match that of CUSP respectively.

Wed 17 Jun

pldi2015-papers
14:00 - 15:40: Research Papers - Parallelism at PLDI Main BLUE (Portland 254-255)
Chair(s): Sara BaghsorkhiIntel Labs
pldi2015-papers14:00 - 14:25
Talk
Murali Krishna EmaniThe University of Edinburgh, Michael O'BoyleUniversity of Edinburgh
Media Attached
pldi2015-papers14:25 - 14:50
Talk
Bin RenPacific Northwest National Laboratories, Youngjoon JoPurdue University, Sriram KrishnamoorthyPacific Northwest National Laboratories, Kunal AgrawalWashington University in St. Louis, Milind KulkarniPurdue University
Media Attached
pldi2015-papers14:50 - 15:15
Talk
Anand VenkatUniversity of Utah, Mary HallUniversity of Utah, Michelle StroutColorado State University
Media Attached
pldi2015-papers15:15 - 15:40
Talk
Dimitrios PrountzosThe University of Texas at Austin, Texas, USA, Roman ManevichBen-Gurion University of the Negev, Keshav PingaliUniversity of Texas, Austin
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