Texturizing PPCG: Supporting Texture Memory in a Polyhedral Compiler

Patwardhan, Abhishek A and Upadrasta, Ramakrishna (2016) Texturizing PPCG: Supporting Texture Memory in a Polyhedral Compiler. In: 23rd IEEE International Conference on High Performance Computing, Data, and Analytics, 19-22 December 2016, Hyderabad.

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In this paper, we discuss techniques to transform sequential programs to texture/surface memory optimized CUDA programs. We achieve this by using PPCG, an automatic paral- lelizing compiler based on the Polyhedral model. We implemented a static analysis in PPCG which validates the semantics of the texturized transformed program. Depending on the results of the analysis, our algorithm chooses to use texture and/or surface memory, and alters the Abstract Syntax Tree accordingly. We also modified the code-generation phase of PPCG to take care of various subtleties. We evaluated the texturization algorithm on the PolyBench (4.2.1 beta) benchmark and observed up to 1.6x speedup with a geometric mean of 1.103X. The title and at many places, the paper uses term Texture memory. But, the optimizations are for Texture and Surface memory.

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IITH Creators:
IITH CreatorsORCiD
Upadrasta, RamakrishnaUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Subjects: Computer science
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 02 Jul 2018 10:25
Last Modified: 02 Jul 2018 10:25
URI: http://raiith.iith.ac.in/id/eprint/4130
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