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Mix and Match: Reorganizing Tasks for Enhancing Data Locality
Xulong Tang
,
Mahmut Taylan Kandemir
, Mustafa Karakoy
Computer Science and Engineering
Institute for Computational and Data Sciences (ICDS)
Research output
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Chapter in Book/Report/Conference proceeding
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Conference contribution
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Dive into the research topics of 'Mix and Match: Reorganizing Tasks for Enhancing Data Locality'. Together they form a unique fingerprint.
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Keyphrases
Data Reuse
100%
Data Locality
100%
Enhanced Data
100%
Mix-and-match
100%
New Task
100%
Compiler-based
66%
Close Proximity
33%
Data Sharing
33%
Spatial Data
33%
Temporal Data
33%
Data Location
33%
Cache Miss
33%
Application Program
33%
Multithreaded Programs
33%
Task Granularity
33%
Strong Locality
33%
Many-core Systems
33%
Locality of Reference
33%
Computer Science
Data Locality
100%
Data Reuse
100%
Target Application
33%
Granularity
33%
Location Data
33%
Close Proximity
33%
Application Program
33%
Execution Order
33%
Manycore System
33%
Multithreaded Program
33%