NDLI: Free launch: optimizing GPU dynamic kernel launches through thread reuse

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Free launch: optimizing GPU dynamic kernel launches through thread reuse

Content Provider	ACM Digital Library
Author	Chen, Guoyang Shen, Xipeng
Abstract	Supporting dynamic parallelism is important for GPU to benefit a broad range of applications. There are currently two fundamental ways for programs to exploit dynamic parallelism on GPU: a software-based approach with software-managed worklists, and a hardware-based approach through dynamic subkernel launches. Neither is satisfactory. The former is complicated to program and is often subject to some load imbalance; the latter suffers large runtime overhead. In this work, we propose free launch, a new software approach to overcoming the shortcomings of both methods. It allows programmers to use subkernel launches to express dynamic parallelism. It employs a novel compiler-based code transformation named subkernel launch removal to replace the subkernel launches with the reuse of parent threads. Coupled with an adaptive task assignment mechanism, the transformation reassigns the tasks in the subkernels to the parent threads with a good load balance. The technique requires no hardware extensions, immediately deployable on existing GPUs. It keeps the programming convenience of the subkernel launch-based approach while avoiding its large runtime overhead. Meanwhile, its superior load balancing makes it outperform manual worklist-based techniques by 3X on average.
Starting Page	407
Ending Page	419
Page Count	13
File Format	PDF
ISBN	9781450340342
DOI	10.1145/2830772.2830818
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-12-05
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Compiler Dynamic parallelism Runtime adaptation Thread reuse Gpu Optimization
Content Type	Text
Resource Type	Article

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