Managing High Performance GPU Clusters

White Papers > Big Data > Managing High Performance GPU Clusters

As of June 2015, the second fastest computer in the world, as measured by the Top500 list employed NVIDIA® GPUs. Of those systems on the same list that use accelerators 60% use NVIDIA GPUs. The performance kick provided by computing accelerators has pushed High Performance Computing (HPC) to new levels. When discussing GPU clusters, the focus is often on the price-to- performance benefits to the end user. The true cost of managing and using GPUs goes far beyond the hardware price, however. Understanding and managing these costs helps provide more efficient and productive systems.

To fully take advantage of NVIDIA GPUs requires several sound strategies. The goal of any HPC resource should be to increase the productivity of researchers and engineers because minimizing time to solution is the goal of many leading HPC installations. Keeping users and developers focused on applications is one of the way to increase productivity and minimize wasted time.

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