NDLI: MATE-CG: A Map Reduce-Like Framework for Accelerating Data-Intensive Computations on Heterogeneous Clusters

Content Provider	IEEE Xplore Digital Library
Author	Wei Jiang Agrawal, G.
Copyright Year	2012
Abstract	Clusters of GPUs have rapidly emerged as the means for achieving extreme-scale, cost-effective, and powerefficient high performance computing. At the same time, high level APIs like map-reduce are being used for developing several types of high-end and/or data-intensive applications. Map-reduce, originally developed for data processing applications, has been successfully used for many classes of applications that involve a significant amount of computations, such as machine learning, image processing, and data mining applications. Because such applications can be accelerated using GPUs (and other accelerators), there has been interest in supporting map-reduce-like APIs on GPUs. However, while the use of map-reduce for a single GPU has been studied, developing map-reduce-like models for programming a heterogeneous CPU-GPU cluster remains an open challenge. This paper presents the MATE-CG system, which is a map reduce-like framework based on the generalized reduction API. We develop support for enabling scalable and efficient implementation of data-intensive applications in a heterogeneous cluster of multi-core CPUs and many-core GPUs. Our contributions are three folds: 1) we port the generalized reduction model on clusters of modern GPUs with a map-reduce-like API, dealing with very large datasets, 2) we further propose three schemes to better utilize the computing power of CPUs and/or GPUs and develop an auto-tuning strategy to achieve the best-possible heterogeneous configuration for iterative applications, 3) we show how analytical models can be used to optimize important parameters in our system. We evaluate our system using three representative data intensive applications and report results on a heterogeneous cluster of 128 CPU cores and 16 GPUs (7168 GPU cores). We show an average speedup of 87× on this cluster over execution with 2 CPU-cores. Our applications also achieve an average improvement of 25% by using CPU cores and GPUs simultaneously, over the best performance achieved from using only one of the types of resources in the cluster.
Starting Page	644
Ending Page	655
File Size	844374
Page Count	12
File Format	PDF
ISBN	9781467309752
ISSN	15302075
DOI	10.1109/IPDPS.2012.65
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Graphics processing unit Runtime Analytical models Acceleration Data processing Computational modeling Multicore processing Heterogeneous Systems Data-Intensive Computing GPUs
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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