Clusters with Gpus under Linux and Windows HPC

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HPC Clusters with GPUs • The right configuration is going to be dependent on the workload • NVIDIA Tesla GPUs for cluster deployments: – Tesla GPU designed for production environments – Memory tested for GPU computing – Tesla S1070 for rack-mounted systems – Tesla M1060 for integrated solutions • Minimum requirements for clusters with Tesla S1070 GPUs: – One CPU core per GPU – One PCI-e x8 slot (x16 Gen2 highly recommended)
CUDA software requirements • Driver: required component to run CUDA applications. • Toolkit: compiler, runtime, libraries (BLAS and FFT). • SDK: collection of examples and documentation Downloadable from http://www.nvidia.com/cuda
Page 1 and 2: Clusters with GPUs under Linux and
Page 3: HPC Clusters • Clusters are very
Page 7 and 8: Linux for GPU clusters
Page 9 and 10: System management for Tesla S1070 n
Page 11 and 12: Windows HPC for GPU clusters Curren
Page 13 and 14: Deployment Means… 1. Getting the
Page 15 and 16: Network Drivers Management Overall
Page 17 and 18: Images, drivers, and all that • A
Page 19 and 20: CUDA Toolkit • To automate the to
Page 21 and 22: Leveraging the GPU • A special en
Page 23: Thank You! • www.nvidia.com/cuda

Clusters with Gpus under Linux and Windows HPC

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