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Benchmarking multi-GPU applications on modern multi-GPU integrated systems

机译:在现代多GPU集成系统上基准测试多GPU应用

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GPUs are very powerful computing accelerators that are often employed in single‐device configuration. However, there is a steadily growing interest in using multiple GPUs in a concurrent way both to overcome the memory limitations of the single device and to further reduce execution times. Until recently, communication among GPUs had been carried out mainly by using networking technologies originally devised for standard CPUs with the CPU playing an active role in the communication. However, new alternatives start to be available in which a moderate number of GPUs are directly connected each other by means of proprietary technologies. We present the results of a set of experiments aimed at assessing the performance of some of these hardware/software platforms using a particularly challenging application as a benchmark. We release its source code to facilitate people interested in reproducing or extending our results.
机译:GPU是非常强大的计算加速器,通常用于单设备配置。 然而,使用以同时克服单个设备的存储器限制并进一步减少执行时间来稳定增长的兴趣。 直到最近,GPU之间的沟通主要是通过使用最初设计的网络技术,该技术与标准CPU具有CPU在通信中发挥积极作用。 然而,新的替代方案开始可用,其中适度数量的GPU通过专有技术直接相互连接。 我们展示了一组实验的结果,旨在评估一些使用特别具有挑战性的应用程序作为基准测试的一些硬件/软件平台的性能。 我们发布其源代码,以促进有兴趣复制或扩展结果的人。

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