Abstract
Architecture designers tend to integrate both CPU and GPU on the same chip to deliver energy-efficient designs. To effectively leverage the power of both CPUs and GPUs on integrated architectures, researchers have recently put substantial efforts into co-running a single application on both the CPU and the GPU of such architectures. However, few studies have been performed to analyze a wide range of parallel computation patterns on such architectures. In this paper, we port all programs in Rodinia benchmark suite and co-run these programs on the integrated architecture. We find that co-running results are not always better than running the application on the CPU only or the GPU only. Among the 20 programs, 3 programs can benefit from co-running, 12 programs using GPU only and 2 programs using CPU only achieve the best performance. The remaining 3 programs show no performance preference for different devices. We also characterize the workload and summarize the patterns for the system insights of co-running on integrated architectures.
Jidong Zhai
Associate Professor
(特别研究员、博士生导师)
