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In the last few years, Graphics Processing Units (GPUs) have become a great tool for massively parallel computing. GPUs are specifically designed for throughput and face several design challenges, specially what is known as the Power and Memory Walls. In these devices, available resources should be used to enhance performance and throughput, as the performance per watt is really high. For massively...
General purpose GPU Computing (GPGPU) has taken off in the past few years, with great promises for increased desktop processing power due to the large number of fast computing cores on high-end graphics cards. Many publications have demonstrated phenomenal performance and have reported speedups as much as 1000× over code running on multi-core CPUs. Other studies have claimed that well-tuned CPU code...
This paper describes the use of CUDA to accelerate the Himeno benchmark on clusters with GPUs. The implementation is designed to optimize memory bandwidth utilization. Our approach achieves over 83% of the theoretical peak bandwidth on a NVIDIA Tesla C1060 GPU and performs at over 50 GFlops. A multi-GPU implementation that utilizes MPI alongside CUDA streams to overlap GPU execution with data transfers...
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