On Power-Performance Characterization of Concurrent Throughput Kernels
IEEE International Symposium on Workload Characterization(2015)
摘要
Growing deployment of power and energy efficient throughput accelerators (GPU) in data centers pushes the envelope of power-performance co-optimization capabilities of GPUs. Realization of exascale computing using accelerators demands further improvements in power efficiency. With hardwired kernel concurrency enablement in accelerators, inter- and intra-workload simultaneous kernels computation predicts increased throughput at lower energy budget. To improve Performance-per-Watt metric of the architectures, a systematic empirical study of real-world throughput workloads (with simultaneous kernel execution) is required. To this end, we propose a multi-kernel throughput workload generation framework that will facilitate aggressive energy and performance management of exascale data centers and will stimulate synergistic power-performance co-optimization of throughput architectures.
更多查看译文
关键词
GPGPU, Power-Performance Analysis, workload characterization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要