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Trace-based manycore partitioning of stream-processing applications

Michalska-Jakubus, Malgorzata; Casale Brunet, Simone; Bezati, Endri; Mattavelli, Marco and Janneck, J. LU (2017) 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 In Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 p.422-426
Abstract

Application performance on these processor array platforms is highly sensitive to how functionality is physically placed on the device, as this choice crucially determines communication latencies and congestion patterns of the on-chip inter-core communication. The problem of identifying the best, or just a good enough, partitioning and placement does not, in general, admit to an analytic solution, and its combinatorial nature makes solving it by pure experimentation impractical. This paper presents an approach that maps stream programs onto processor arrays using trace analysis as a technique for evaluating candidate solutions and for suggesting alternatives.

Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
dataflow, execution trace, manycore, partitioning, profiling
in
Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
pages
5 pages
publisher
IEEE Computer Society
conference name
50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
external identifiers
  • scopus:85016319410
ISBN
9781538639542
DOI
10.1109/ACSSC.2016.7869073
language
English
LU publication?
yes
id
1924fe38-008f-4b3e-86db-8b93658f1491
date added to LUP
2017-04-12 15:08:14
date last changed
2018-01-07 11:59:11
@inproceedings{1924fe38-008f-4b3e-86db-8b93658f1491,
  abstract     = {<p>Application performance on these processor array platforms is highly sensitive to how functionality is physically placed on the device, as this choice crucially determines communication latencies and congestion patterns of the on-chip inter-core communication. The problem of identifying the best, or just a good enough, partitioning and placement does not, in general, admit to an analytic solution, and its combinatorial nature makes solving it by pure experimentation impractical. This paper presents an approach that maps stream programs onto processor arrays using trace analysis as a technique for evaluating candidate solutions and for suggesting alternatives.</p>},
  author       = {Michalska-Jakubus, Malgorzata and Casale Brunet, Simone and Bezati, Endri and Mattavelli, Marco and Janneck, J.},
  booktitle    = {Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016},
  isbn         = {9781538639542},
  keyword      = {dataflow,execution trace,manycore,partitioning,profiling},
  language     = {eng},
  month        = {03},
  pages        = {422--426},
  publisher    = {IEEE Computer Society},
  title        = {Trace-based manycore partitioning of stream-processing applications},
  url          = {http://dx.doi.org/10.1109/ACSSC.2016.7869073},
  year         = {2017},
}