NDLI: Optimizing the use of GPU memory in applications with large data sets

Content Provider	IEEE Xplore Digital Library
Author	Satish, N. Sundaram, N. Keutzer, K.
Copyright Year	2009
Description	Author affiliation: University of California, Berkeley CA USA (Sundaram, N.; Keutzer, K.) \|\| University of California, Berkeley CA, USA (Satish, N.)
Abstract	With General Purpose programmable GPUs becoming more and more popular, automated tools are needed to bridge the gap between achievable performance from highly parallel architectures and the performance required in applications. In this paper, we concentrate on improving GPU memory management for applications with large and intermediate data sets that do not completely fit in GPU memory. For such applications, the movement of the extra data to CPU memory must be carefully managed. In particular, we focus on solving the joint task scheduling and data transfer scheduling problem posed in [1], and propose an algorithm that gives close to optimal results (as measured by running simulated annealing overnight) in terms of the amount of data transferred for image processing benchmarks such as edge detection and Convolutional Neural Networks. Our results enable a reduction of up to 30× in the amount of data transfers compared to an unoptimized implementation. They are up to 2× better than the methods previously proposed in [1] and less than 16% away from the optimal solution.
Starting Page	408
Ending Page	418
File Size	282314
Page Count	11
File Format	PDF
ISBN	9781424449224
e-ISBN	9781424449217
DOI	10.1109/HIPC.2009.5433185
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-16
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bandwidth Memory management Parallel architectures Scheduling algorithm Image processing Neural networks Cellular neural networks Moore's Law Bridges Particle measurements
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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