Frank Feinbube, Peter Tröger, Johannes Henning, A. Polze
{"title":"Leveraging Hybrid Hardware in New Ways - The GPU Paging Cache","authors":"Frank Feinbube, Peter Tröger, Johannes Henning, A. Polze","doi":"10.1109/ICPADS.2013.49","DOIUrl":null,"url":null,"abstract":"Modern server and desktop systems combine multiple computational cores and accelerator devices into a hybrid architecture. GPUs as one class of such devices provide dedicated processing power and memory capacities for data parallel computation of 2D and 3D graphics. Although these cards have demonstrated their applicability in a variety of areas, they are almost exclusively used by special purpose software. If such software is not running, the accelerator resources of the hybrid system remain unused. In this paper, we present an operating system extension that allows leveraging the GPU accelerator memory for operating system purposes. Our approach utilizes graphics card memory as cache for virtual memory pages, which can improve the overall system responsiveness, especially under heavy load. Our prototypical implementation for Windows proves the potential of such an approach, but identifies also significant preconditions for a widespread adoption in desktop systems.","PeriodicalId":160979,"journal":{"name":"2013 International Conference on Parallel and Distributed Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Parallel and Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPADS.2013.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Modern server and desktop systems combine multiple computational cores and accelerator devices into a hybrid architecture. GPUs as one class of such devices provide dedicated processing power and memory capacities for data parallel computation of 2D and 3D graphics. Although these cards have demonstrated their applicability in a variety of areas, they are almost exclusively used by special purpose software. If such software is not running, the accelerator resources of the hybrid system remain unused. In this paper, we present an operating system extension that allows leveraging the GPU accelerator memory for operating system purposes. Our approach utilizes graphics card memory as cache for virtual memory pages, which can improve the overall system responsiveness, especially under heavy load. Our prototypical implementation for Windows proves the potential of such an approach, but identifies also significant preconditions for a widespread adoption in desktop systems.