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A case for core-assisted bottleneck acceleration in GPUs
2015
Proceedings of the 42nd Annual International Symposium on Computer Architecture - ISCA '15
Modern Graphics Processing Units (GPUs) are well provisioned to support the concurrent execution of thousands of threads. Unfortunately, di erent bottlenecks during execution and heterogeneous application requirements create imbalances in utilization of resources in the cores. For example, when a GPU is bottlenecked by the available o -chip memory bandwidth, its computational resources are often overwhelmingly idle, waiting for data from memory to arrive. This paper introduces the Core-Assisted
doi:10.1145/2749469.2750399
dblp:conf/isca/VijaykumarPJ0AD15
fatcat:vow55cmt3zhlxmg5o3x2lxx6ri