Sunjun Hwang, Jin Choi, Seohwan Yoo, Hayeon Park, Chang-Gun Lee
{"title":"Hardware Interrupt and CPU Contention aware CPU/GPU Co-Scheduling on Multi-Cluster System","authors":"Sunjun Hwang, Jin Choi, Seohwan Yoo, Hayeon Park, Chang-Gun Lee","doi":"10.1109/ICICT55905.2022.00028","DOIUrl":null,"url":null,"abstract":"As a co-processor for data-parallel processing and graphics, the GPU plays an important role in recent platforms. GPU is regarded as an input/output device on the CPU-GPU heterogeneous board and generates a hardware interrupt to communicate with the CPU. Since the CPU delays the execution of the GPU workload to process such a hardware interrupt, the hardware interrupt is a factor that degrades the GPU performance. In this paper, we propose a method to improve the processing performance of GPU by separating the CPU core that handles hardware interrupts from the CPU core that handles GPU tasks in the CPU-GPU heterogeneous architecture. In addition, CPU contention was resolved by separating the CPU core that processes the CPU task from the GPU task.","PeriodicalId":273927,"journal":{"name":"2022 5th International Conference on Information and Computer Technologies (ICICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Information and Computer Technologies (ICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT55905.2022.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
As a co-processor for data-parallel processing and graphics, the GPU plays an important role in recent platforms. GPU is regarded as an input/output device on the CPU-GPU heterogeneous board and generates a hardware interrupt to communicate with the CPU. Since the CPU delays the execution of the GPU workload to process such a hardware interrupt, the hardware interrupt is a factor that degrades the GPU performance. In this paper, we propose a method to improve the processing performance of GPU by separating the CPU core that handles hardware interrupts from the CPU core that handles GPU tasks in the CPU-GPU heterogeneous architecture. In addition, CPU contention was resolved by separating the CPU core that processes the CPU task from the GPU task.