TY - GEN
T1 - Using the cell broadband engine and NVIDIA 8800 GPU for computational science applications
T2 - 2008 International Symposium on Applied Computing and Computational Sciences, ACCS 2008
AU - McCreath, Eric C.
AU - Zein, Ahmed El
AU - Imholz, Jeremy
AU - Rendell, Alistair P.
AU - Wong, Emily
N1 - Publisher Copyright:
© 2008 Global Information Publisher (H.K) Co., Limited. All rights reserved.
PY - 2008
Y1 - 2008
N2 - The NVIDIA 8800 Graphics Processing Unit (GPU) and the Cell Broadband Engine employ a vast amount of parallelism to produce low cost high performance systems which dwarf standard desktop processing units in terms of floating point calculations. These systems offer great potential for computational science applications. This paper compares the programming model, implementation strategies and realised performance achieved on these two systems for implementing a simple particle dynamics simulation code. Both systems were found to give considerable performance improvements over high-end uni-processor machines. The Synergistic Processing Elements (SPE), on the Cell, can not directly access main memory. This complicates initial implementation compared to the NVIDIA GPU, however, fully exploiting the complex architectures of both systems is equally challenging.
AB - The NVIDIA 8800 Graphics Processing Unit (GPU) and the Cell Broadband Engine employ a vast amount of parallelism to produce low cost high performance systems which dwarf standard desktop processing units in terms of floating point calculations. These systems offer great potential for computational science applications. This paper compares the programming model, implementation strategies and realised performance achieved on these two systems for implementing a simple particle dynamics simulation code. Both systems were found to give considerable performance improvements over high-end uni-processor machines. The Synergistic Processing Elements (SPE), on the Cell, can not directly access main memory. This complicates initial implementation compared to the NVIDIA GPU, however, fully exploiting the complex architectures of both systems is equally challenging.
UR - http://www.scopus.com/inward/record.url?scp=84945959218&partnerID=8YFLogxK
M3 - Conference contribution
T3 - Advances in Applied Computing and Computational Sciences - Proceedings of International Symposium on Applied Computing and Computational Sciences, ACCS 2008
SP - 74
EP - 80
BT - Advances in Applied Computing and Computational Sciences - Proceedings of International Symposium on Applied Computing and Computational Sciences, ACCS 2008
A2 - Yu, Lean
A2 - Lai, Kin Keung
PB - Global Information Publisher (H.K) Co., Limited
Y2 - 1 August 2008 through 3 August 2008
ER -