Multi-GPU nodes are increasingly common in the rapidly evolving landscape of exascale supercomputers. On these systems, GPUs on the same node are connected through dedicated networks, with bandwidths up to a few terabits per second. However, gauging performance expectations and maximizing system efficiency is challenging due to different technologies, design options, and software layers. This paper comprehensively characterizes three supercomputers - Alps, Leonardo, and LUMI - each with a unique architecture and design. We focus on performance evaluation of intra-node and inter-node interconnects on up to 4,096 GPUs, using a mix of intra-node and inter-node benchmarks. By analyzing its limitations and opportunities, we aim to offer practical guidance to researchers, system architects, and software developers dealing with multi-GPU supercomputing. Our results show that there is untapped bandwidth, and there are still many opportunities for optimization, ranging from network to software ...
Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects / De Sensi, D., Pichetti, L., Vella, F., De Matteis, T., Ren, Z., Fusco, L., Turisini, M., Cesarini, D., Lust, K., Trivedi, A., Roweth, D., Spiga, F., Di Girolamo, S.. - (2024), pp. 1-15. (2024 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2024 Georgia World Congress Center, usa November 17 2024-November 22 2024) [10.1109/SC41406.2024.00039].
Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects
Flavio Vella
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2024-01-01
Abstract
Multi-GPU nodes are increasingly common in the rapidly evolving landscape of exascale supercomputers. On these systems, GPUs on the same node are connected through dedicated networks, with bandwidths up to a few terabits per second. However, gauging performance expectations and maximizing system efficiency is challenging due to different technologies, design options, and software layers. This paper comprehensively characterizes three supercomputers - Alps, Leonardo, and LUMI - each with a unique architecture and design. We focus on performance evaluation of intra-node and inter-node interconnects on up to 4,096 GPUs, using a mix of intra-node and inter-node benchmarks. By analyzing its limitations and opportunities, we aim to offer practical guidance to researchers, system architects, and software developers dealing with multi-GPU supercomputing. Our results show that there is untapped bandwidth, and there are still many opportunities for optimization, ranging from network to software ...| File | Dimensione | Formato | |
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