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 Times are displayed in time zone: Tijuana, Baja California change
14:00 - 15:40 | |||
14:00 25mTalk | Celebrating Diversity: A Mixture of Experts Approach for Runtime Mapping in Dynamic Environments Research Papers Media Attached | ||
14:25 25mTalk | Efficient Execution of Recursive Programs on Commodity Vector Hardware Research Papers Bin RenPacific Northwest National Laboratories, Youngjoon JoPurdue University, Sriram KrishnamoorthyPacific Northwest National Laboratories, Kunal AgrawalWashington University in St. Louis, Milind KulkarniPurdue University Media Attached | ||
14:50 25mTalk | Loop and Data Transformations for Sparse Matrix Code Research Papers Anand VenkatUniversity of Utah, Mary HallUniversity of Utah, Michelle StroutColorado State University Media Attached | ||
15:15 25mTalk | Synthesizing Parallel Graph Programs via Automated Planning Research Papers Dimitrios PrountzosThe University of Texas at Austin, Texas, USA, Roman ManevichBen-Gurion University of the Negev, Keshav PingaliUniversity of Texas, Austin Media Attached |