Accelerating S3D: A GPGPU case study

Conference · Thu Jan 01 00:00:00 EST 2009

OSTI ID:963944

Spafford, Kyle L ^[1]; Meredith, Jeremy S ^[1]; Vetter, Jeffrey S ^[1]; Chen, Jackie ^[2]; Grout, Ray W ^[1]; Sankaran, Ramanan ^[1]

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1. ORNL
2. Sandia National Laboratories (SNL)

The graphics processor (GPU) has evolved into an appealing choice for high performance computing due to its superior memory bandwidth, raw processing power, and flexible programmability. As such, GPUs represent an excellent platform for accelerating scientific applications. This paper explores a methodology for identifying applications which present significant potential for acceleration. In particular, this work focuses on experiences from accelerating S3D, a high-fidelity turbulent reacting flow solver. The acceleration process is examined from a holistic viewpoint, and includes details that arise from different phases of the conversion. This paper also addresses the issue of floating point accuracy and precision on the GPU, a topic of immense importance to scientific computing. Several performance experiments are conducted, and results are presented from the NVIDIA Tesla C1060 GPU. We generalize from our experiences to provide a roadmap for deploying existing scientific applications on heterogeneous GPU platforms.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Center for Computational Sciences (NCCS)
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: DE-AC05-00OR22725
• OSTI ID: 963944
• Resource Relation: Conference: European conference on parallel computing - heteropar workshop, Delft, Netherlands, 20090825, 20090825
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
COMPUTER GRAPHICS
COMPUTER CALCULATIONS
PERFORMANCE
TURBULENT FLOW
ACCURACY