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ASHA: An adaptive shared-memory sharing architecture for multi-programmed GPUs
, Article Microprocessors and Microsystems ; Volume 46 , 2016 , Pages 264-273 ; 01419331 (ISSN) ; Samavatian, M. H ; Sarbazi Azad, H ; Sharif University of Technology
Elsevier B.V
2016
Abstract
Spatial multi-programming is one of the most efficient multi-programming methods on Graphics Processing Units (GPUs). This multi-programming scheme generates variety in resource requirements of stream multiprocessors (SMs) and creates opportunities for sharing unused portions of each SM resource with other SMs. Although this approach drastically improves GPU performance, in some cases it leads to performance degradation due to the shortage of allocated resource to each program. Considering shared-memory as one of the main bottlenecks of thread-level parallelism (TLP), in this paper, we propose an adaptive shared-memory sharing architecture, called ASHA. ASHA enhances spatial...