Evaluating integrated graphics processors for data center workloads

Sangman Kim, Indrajit Roy, V. Talwar
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引用次数: 8

Abstract

More than 90% of consumer computers use integrated graphics processors. In these processors, the CPU and the GPU share the same physical memory. Due to high density, good power efficiency, and low cost, integrated graphics processors are promising candidates for next-generation micro-servers and, hence, data-center workloads. While discrete graphics processors have been extensively studied, there is very little work on characterizing integrated GPUs. This paper is a step towards understanding the power and performance of integrated GPUs. Our results reveal many architectural caveats that programmers need to be aware of to exploit integrated GPUs: memory contention between the CPU and GPU, workload dependent energy efficiency, and data transfer tradeoffs.
评估数据中心工作负载的集成图形处理器
超过90%的消费电脑使用集成图形处理器。在这些处理器中,CPU和GPU共享相同的物理内存。由于高密度、良好的功率效率和低成本,集成图形处理器是下一代微型服务器和数据中心工作负载的理想选择。虽然离散图形处理器已经得到了广泛的研究,但对集成图形处理器的特性研究却很少。本文是了解集成gpu的功率和性能的一步。我们的研究结果揭示了程序员在利用集成GPU时需要注意的许多架构警告:CPU和GPU之间的内存争用、工作负载相关的能源效率和数据传输权衡。
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