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» Performance study of mapping irregular computations on GPUs
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IPPS
2009
IEEE
15 years 4 months ago
Exploring the multiple-GPU design space
Graphics Processing Units (GPUs) have been growing in popularity due to their impressive processing capabilities, and with general purpose programming languages such as NVIDIA’s...
Dana Schaa, David R. Kaeli
73
Voted
IEEEPACT
2008
IEEE
15 years 4 months ago
Mars: a MapReduce framework on graphics processors
We design and implement Mars, a MapReduce framework, on graphics processors (GPUs). MapReduce is a distributed programming framework originally proposed by Google for the ease of ...
Bingsheng He, Wenbin Fang, Qiong Luo, Naga K. Govi...
ICS
1999
Tsinghua U.
15 years 1 months ago
Improving memory hierarchy performance for irregular applications
The performance of irregular applications on modern computer systems is hurt by the wide gap between CPU and memory speeds because these applications typically underutilize multi-...
John M. Mellor-Crummey, David B. Whalley, Ken Kenn...
FPGA
2010
ACM
294views FPGA» more  FPGA 2010»
15 years 2 months ago
Axel: a heterogeneous cluster with FPGAs and GPUs
This paper describes a heterogeneous computer cluster called Axel. Axel contains a collection of nodes; each node can include multiple types of accelerators such as FPGAs (Field P...
Kuen Hung Tsoi, Wayne Luk
PPOPP
2010
ACM
15 years 6 months ago
Model-driven autotuning of sparse matrix-vector multiply on GPUs
We present a performance model-driven framework for automated performance tuning (autotuning) of sparse matrix-vector multiply (SpMV) on systems accelerated by graphics processing...
Jee W. Choi, Amik Singh, Richard W. Vuduc