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ITS Cluster Finding Algorithm on GPU
ITS cluster finding algorithm is one of the data reduction algorithms at ALICE. It needs to be processed fast due to a high amount of data readout from the detector. A variety of platforms were studied for the system design. My work is to design, implement and benchmark this algorithm on a GPU platf...
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Lenguaje: | eng |
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2014
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Acceso en línea: | http://cds.cern.ch/record/1748452 |
_version_ | 1780943000006819840 |
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author | Changaival, Boonyarit |
author_facet | Changaival, Boonyarit |
author_sort | Changaival, Boonyarit |
collection | CERN |
description | ITS cluster finding algorithm is one of the data reduction algorithms at ALICE. It needs to be processed fast due to a high amount of data readout from the detector. A variety of platforms were studied for the system design. My work is to design, implement and benchmark this algorithm on a GPU platform. GPU is one of many platform that promote parallel computing. A high-end GPU can contain over 2000 processing cores comparing to the commodity CPUs which have only four cores. The program is written in C and CUDA library. The throughput (Number of events per second) is used as a metric to measure the performance. With the latest implementation, the throughput was increased by a factor of 5. |
id | cern-1748452 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2014 |
record_format | invenio |
spelling | cern-17484522019-09-30T06:29:59Zhttp://cds.cern.ch/record/1748452engChangaival, BoonyaritITS Cluster Finding Algorithm on GPUComputing and ComputersITS cluster finding algorithm is one of the data reduction algorithms at ALICE. It needs to be processed fast due to a high amount of data readout from the detector. A variety of platforms were studied for the system design. My work is to design, implement and benchmark this algorithm on a GPU platform. GPU is one of many platform that promote parallel computing. A high-end GPU can contain over 2000 processing cores comparing to the commodity CPUs which have only four cores. The program is written in C and CUDA library. The throughput (Number of events per second) is used as a metric to measure the performance. With the latest implementation, the throughput was increased by a factor of 5.CERN-STUDENTS-Note-2014-015oai:cds.cern.ch:17484522014 |
spellingShingle | Computing and Computers Changaival, Boonyarit ITS Cluster Finding Algorithm on GPU |
title | ITS Cluster Finding Algorithm on GPU |
title_full | ITS Cluster Finding Algorithm on GPU |
title_fullStr | ITS Cluster Finding Algorithm on GPU |
title_full_unstemmed | ITS Cluster Finding Algorithm on GPU |
title_short | ITS Cluster Finding Algorithm on GPU |
title_sort | its cluster finding algorithm on gpu |
topic | Computing and Computers |
url | http://cds.cern.ch/record/1748452 |
work_keys_str_mv | AT changaivalboonyarit itsclusterfindingalgorithmongpu |