NDLI: Matchmaking Applications and Partitioning Strategies for Efficient Execution on Heterogeneous Platforms

Content Provider	IEEE Xplore Digital Library
Author	Jie Shen Varbanescu, A.L. Martorell, X. Sips, H.
Copyright Year	2015
Description	Author affiliation: Barcelona Supercomput. Center, Univ. Politec. de Catalunya, Barcelona, Spain (Martorell, X.) \|\| Parallel & Distrib. Syst. Group, Delft Univ. of Technol., Delft, Netherlands (Jie Shen; Sips, H.) \|\| Inf. Inst., Univ. of Amsterdam, Amsterdam, Netherlands (Varbanescu, A.L.)
Abstract	Heterogeneous platforms are mixes of different processing units. The key factor to their efficient usage is workload partitioning. Both static and dynamic partitioning strategies have been defined in previous work, but their applicability and performance differ significantly depending on the application to execute. In this paper, we propose an application-driven method to select the best partitioning strategy for a given workload. To this end, we define an application classification based on the application kernel structure -- i.e., The number of kernels in the application and their execution flow. We also enable five different partitioning strategies, which mix the best features of both static and dynamic approaches. We further define the performance-driven ranking of all suitable strategies for each application class. Finally, we match the best partitioning to a given application by simply determining its class and selecting the best ranked strategy for that class. We test the matchmaking on six representative applications, and demonstrate that the defined performance ranking is correct. Moreover, by choosing the best performing partitioning strategy, we can significantly improve application performance, leading to average speedup of 3.0x/5.3x over the Only-GPU/Only-CPU execution, respectively.
Starting Page	560
Ending Page	569
File Size	540941
Page Count	10
File Format	PDF
ISBN	9781467375870
ISSN	01903918
DOI	10.1109/ICPP.2015.65
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Runtime Hardware Graphics processing units Instruction sets Computational modeling Performance Heterogeneous platforms Workload partitioning Application classification Applicability
Content Type	Text
Resource Type	Article

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