Operator and Workflow Optimization for High-Performance Analytics
| Data(s) |
15/03/2016
|
|---|---|
| Resumo |
We make a case for studying the impact of intra-node parallelism on the performance of data analytics. We identify four performance optimizations that are enabled by an increasing number of processing cores on a chip. We discuss the performance impact of these opimizations on two analytics operators and we identify how these optimizations affect each another. |
| Formato |
application/pdf |
| Identificador | |
| Idioma(s) |
eng |
| Direitos |
info:eu-repo/semantics/openAccess |
| Fonte |
Vandierendonck , H , Murphy , K L , Arif , M , Sun , J & Nikolopoulos , D S 2016 , ' Operator and Workflow Optimization for High-Performance Analytics ' Paper presented at 1st International Workshop on Multi-Engine Data Analytics (MEDAL) , Bordeaux , France , 15/03/2016 - 15/03/2016 , . |
| Tipo |
conferenceObject |
