A Workload Balanced MapReduce Framework on GPU Platforms

Bibliographic Details
Main Author: Zhang, Yue
Language:English
Published: Wright State University / OhioLINK 2015
Subjects:
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=wright1450180042
id ndltd-OhioLink-oai-etd.ohiolink.edu-wright1450180042
record_format oai_dc
spelling ndltd-OhioLink-oai-etd.ohiolink.edu-wright14501800422021-08-03T06:34:36Z A Workload Balanced MapReduce Framework on GPU Platforms Zhang, Yue Computer Engineering Computer Engineering The MapReduce framework is a programming model proposed by Google to process large datasets. It is an efficient framework that can be used in many areas, such as social network, scientific research, electronic business, etc. Hence, more and more MapReduce frameworks are implemented on different platforms, including Phoenix (based on multicore CPU), MapCG (based on GPU), and StreamMR (based on GPU). However, these MapReduce frameworks have limitations, and they cannot handle the collision problem in the map phase, and the unbalanced workload problems in the reduce phase. To improve the performance of the MapReduce framework on GPGPUs, in this thesis, a workload balance MapReduce framework (B_MapCG) on GPUs is proposed and developed based on the MapCG framework, to reduce the number of collisions while inserting key-value pairs in the map phase, and to handle the unbalanced workload problems in the reduce phase. The proposed B_MapCG framework is evaluated on the Tesla K40 GPU with four benchmarks and eight different datasets. The experimental results showed that the B_MapCG framework achieved big performance improvements for all the four test benchmarks both in the map phase and the reduce phase compared with MapCG. 2015-12-21 English text Wright State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=wright1450180042 http://rave.ohiolink.edu/etdc/view?acc_num=wright1450180042 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Computer Engineering
Computer Engineering
spellingShingle Computer Engineering
Computer Engineering
Zhang, Yue
A Workload Balanced MapReduce Framework on GPU Platforms
author Zhang, Yue
author_facet Zhang, Yue
author_sort Zhang, Yue
title A Workload Balanced MapReduce Framework on GPU Platforms
title_short A Workload Balanced MapReduce Framework on GPU Platforms
title_full A Workload Balanced MapReduce Framework on GPU Platforms
title_fullStr A Workload Balanced MapReduce Framework on GPU Platforms
title_full_unstemmed A Workload Balanced MapReduce Framework on GPU Platforms
title_sort workload balanced mapreduce framework on gpu platforms
publisher Wright State University / OhioLINK
publishDate 2015
url http://rave.ohiolink.edu/etdc/view?acc_num=wright1450180042
work_keys_str_mv AT zhangyue aworkloadbalancedmapreduceframeworkongpuplatforms
AT zhangyue workloadbalancedmapreduceframeworkongpuplatforms
_version_ 1719439854400438272