Mars-HD : a high performance computing systems for many-core processors
Mars-HD was built over Mars, a GPU MapReduce Framework, to allow it to work in the Hadoop cluster. This gives rise to the ability for multiple GPUs to work together in a distributed cloud system. As data processing becomes more crucial to understanding the trends of the world, it becomes es...
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sg-ntu-dr.10356-592632023-03-03T20:26:14Z Mars-HD : a high performance computing systems for many-core processors Lim, Chun Leng School of Computer Engineering Parallel and Distributed Computing Centre He BingSheng DRNTU::Engineering::Computer science and engineering::Computer systems organization::Performance of systems Mars-HD was built over Mars, a GPU MapReduce Framework, to allow it to work in the Hadoop cluster. This gives rise to the ability for multiple GPUs to work together in a distributed cloud system. As data processing becomes more crucial to understanding the trends of the world, it becomes essential to process these incoming data in the shortest time possible. Thus, the power of the clusters is necessary. Mars-HD successfully ensure scalability of the Mars framework, by building it directly on top of Hadoop MapReduce Framework, allowing Hadoop to perform the function of load balancing and then sends the data over to Mars to be processed and outputs the result. Performance on Mars-HD is not on par with Mars due to the overhead in the Hadoop Framework, however, with the use of Mars-HD on an input data of the correct size, the performance difference can be reduced and achieve speedup. Bachelor of Engineering (Computer Science) 2014-04-28T05:42:26Z 2014-04-28T05:42:26Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/59263 en Nanyang Technological University 22 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computer systems organization::Performance of systems Lim, Chun Leng Mars-HD : a high performance computing systems for many-core processors |
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Mars-HD was built over Mars, a GPU MapReduce Framework, to allow it to work in the
Hadoop cluster. This gives rise to the ability for multiple GPUs to work together in a
distributed cloud system. As data processing becomes more crucial to understanding the trends
of the world, it becomes essential to process these incoming data in the shortest time possible.
Thus, the power of the clusters is necessary. Mars-HD successfully ensure scalability of the
Mars framework, by building it directly on top of Hadoop MapReduce Framework, allowing
Hadoop to perform the function of load balancing and then sends the data over to Mars to be
processed and outputs the result. Performance on Mars-HD is not on par with Mars due to the
overhead in the Hadoop Framework, however, with the use of Mars-HD on an input data of
the correct size, the performance difference can be reduced and achieve speedup. |
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School of Computer Engineering |
author_facet |
School of Computer Engineering Lim, Chun Leng |
format |
Final Year Project |
author |
Lim, Chun Leng |
author_sort |
Lim, Chun Leng |
title |
Mars-HD : a high performance computing systems for many-core processors |
title_short |
Mars-HD : a high performance computing systems for many-core processors |
title_full |
Mars-HD : a high performance computing systems for many-core processors |
title_fullStr |
Mars-HD : a high performance computing systems for many-core processors |
title_full_unstemmed |
Mars-HD : a high performance computing systems for many-core processors |
title_sort |
mars-hd : a high performance computing systems for many-core processors |
publishDate |
2014 |
url |
http://hdl.handle.net/10356/59263 |
_version_ |
1759856514705653760 |