A case for core-assisted bottleneck acceleration in GPUs

Nandita Vijaykumar, Gennady Pekhimenko, Adwait Jog, Abhishek Bhowmick, Rachata Ausavarungnirun, Chita Das, Mahmut Kandemir, Todd C. Mowry, Onur Mutlu
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
more » ... Bottleneck Acceleration (CABA) framework that employs idle on-chip resources to alleviate di erent bottlenecks in GPU execution. CABA provides exible mechanisms to automatically generate "assist warps" that execute on GPU cores to perform speci c tasks that can improve GPU performance and e ciency. CABA enables the use of idle computational units and pipelines to alleviate the memory bandwidth bottleneck, e.g., by using assist warps to perform data compression to transfer less data from memory. Conversely, the same framework can be employed to handle cases where the GPU is bottlenecked by the available computational units, in which case the memory pipelines are idle and can be used by CABA to speed up computation, e.g., by performing memoization using assist warps. We provide a comprehensive design and evaluation of CABA to perform e ective and exible data compression in the GPU memory hierarchy to alleviate the memory bandwidth bottleneck. Our extensive evaluations show that CABA, when used to implement data compression, provides an average performance improvement of 41.7% (as high as 2.6X) across a variety of memory-bandwidth-sensitive GPGPU applications.
doi:10.1145/2749469.2750399 dblp:conf/isca/VijaykumarPJ0AD15 fatcat:vow55cmt3zhlxmg5o3x2lxx6ri