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| Hauptseite > Publikationsdatenbank > Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric |
| Hauptseite > Publikationsdatenbank > Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric |
| Contribution to a conference proceedings | FZJ-2025-00766 |
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2024
IEEE
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Please use a persistent id in citations: doi:10.1109/SCW63240.2024.00079
Abstract: Modern GPU systems are constantly evolving tomeet the needs of computing-intensive applications in scientificand machine learning domains. However, there is typically a gapbetween the hardware capacity and the achievable applicationperformance. This work aims to provide a better understandingof the Infinity Fabric interconnects on AMD GPUs and CPUs. Wepropose a test and evaluation methodology for characterizing theperformance of data movements on multi-GPU systems, stressingdifferent communication options on AMD MI250X GPUs, includ-ing point-to-point and collective communication, and memoryallocation strategies between GPUs, as well as the host CPU.In a single-node setup with four GPUs, we show that directpeer-to-peer memory accesses between GPUs and utilization ofthe RCCL library outperform MPI-based solutions in terms ofmemory/communication latency and bandwidth. Our test andevaluation method serves as a base for validating memory andcommunication strategies on a system and improving applicationson AMD multi-GPU computing systems.
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