Paper Info
Title
On Predicting the Impact of Resource Redistributions in Streaming Applications
Abstract
We propose a method for black-box performance modelling of executions of data-parallel array operations on shared memory multi-core systems. Black-box performance modelling refers to the idea that the source code as well as its attendant compilation process are completely independent from the modelling itself. The performance model exclusively builds on observable behaviour available when executing the compiled code. From given input characteristics and previous runtime observations we predict overall runtimes in relation to the number of cores that can be exclusively used for the task. We show that using our technique our model's runtime predictions fall within 10% of the observed runtime. The paper describes the rationale as well as the technical details of the approach. We discuss several design choices of the technique and we experimentally explore their implications. We also discuss an online implementation of the proposed approach and we show that the model can be used very effectively in a streaming context.
Year
DOI
Venue
2014
10.1145/2627373.2627386
ARRAY@PLDI
Keywords
Field
DocType
design,experimentation,compilers,measurement,languages,performance,static analysis,multiple dispatch,type inference
Observable,Shared memory,Computer science,Source code,Multiple dispatch,Static analysis,Dynamic dispatch,Type inference,Compiled language,Theoretical computer science,Distributed computing
Conference
Citations 
PageRank 
References 
0
0.34
9
Authors
2
Name
Order
Citations
PageRank
Merijn Verstraaten1564.96
Sven-Bodo Scholz211.37