Presentation
GPU cluster for High-Performance Computing (Test of Time Award)
DescriptionGPU Cluster for High Performance Computing Authors: Zhe Fan, Feng Qiu, Arie Kaufman, Suzanne Yoakum-Stover Center For Visual Computing and Department of Computer Science Stony Brook University, Stony Brook, NY, USA This paper was published at SC04 This seminal work focuses on the design of a large GPU cluster that demonstrates the usability, scalability and excellent price-to-performance ratio of GPU devices for executing High Performance Computing (HPC) applications at scale. The authors assembled a cluster with 32 dual CPU-GPU computation nodes connected by a 1 Gigabit Ethernet switch. They developed a parallel flow simulation using the Lattice Boltzmann Model from Computational Fluid Dynamics. They simulated the dispersion of airborne contaminants in the Times Square area of New York City, achieving impressive speed-up over a standard CPU-only parallel implementation. Building upon this result, the authors discussed several other potential applications of their GPU cluster, such as cellular automata, PDE solvers, and Finite Element Methods. Several papers had previously advocated the use of a single GPU to speed-up numerical computations (such as matrix multiplication). But back in 2004, this work was the first to demonstrate the full potential of GPU devices for large-scale applications. The rest is history: 20 years later, GPU devices have become omnipresent in HPC and represent over 95% of the peak performance of the majority of the fastest supercomputers in the world, including number 1 Frontier at Oak Ridge National Laboratory, TN, USA.
Event Type
Awards and Award Talks
TimeTuesday, 19 November 20243:30pm - 4:15pm EST
LocationExhibit Hall A3
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