🤖 AI Summary
本文设计并实现了一个基于NVIDIA NVSHMEM的多GPU并发队列系统，通过Bellman-Ford算法评估其性能，实现了相比单GPU显著的速度提升。
📝 Abstract
This paper presents the design and implementation of a multi-GPU concurrent queue system using NVIDIA's NVSHMEM. The Bellman-Ford algorithm is used as a case study to evaluate the performance of the proposed concurrent FIFO queue, with this multi-GPU implementation being the first known instance of its kind. Experimental results demonstrate that the multi-GPU queue implementation achieves a maximum speedup of 3.92x and an average speedup of 3.04x over the singleGPU baseline on four NVIDIA A100 GPUs. When applied to the Bellman-Ford Single-Source Shortest Path (SSSP) algorithm, the multi-GPU system achieves a maximum speedup of 3.03x and an average speedup of 2.65x compared to the single-GPU implementation, tested on 10 graphs of different kinds taken from the SuiteSparse Matrix Collection.