Static Graphs for Coding Productivity in OpenACC

Conference · 01 December 2021

DOI:https://doi.org/10.1109/HiPC53243.2021.00050· OSTI ID:1883754

Toledo, Leonel ^[1]; Valero Lara, Pedro ^[2]; Vetter, Jeffrey ^[2]; Pena, Antonio ^[1]

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1. Barcelona Supercomputing Center
2. ORNL

The main contribution of this work is to increase the coding productivity for GPU programming by using the concept of Static Graphs. To do so, we have combined the new CUDA Graph API with the OpenACC programming model. We use as test cases a well-known and widely used problems in HPC and AI: the Particle Swarm Optimization. We complement the OpenACC functionality with the use of CUDA Graph, achieving accelerations of more than one order of magnitude, and a performance very close to a reference and optimized CUDA code. Finally, we propose a new specification to incorporate the concept of Static Graphs into the OpenACC specification.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1883754
• Resource Relation: Conference: 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC) - Virtual, , India - 12/17/2021 5:00:00 AM-8/20/2022 4:00:00 AM
• Country of Publication: United States
• Language: English