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Adapting convergent scheduling using machine learning (citation_only)

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Diego PuppinAuthors Info & Claims

PPoPP '03: Proceedings of the ninth ACM SIGPLAN symposium on Principles and practice of parallel programming

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https://doi.org/10.1145/781498.781521

Published: 11 June 2003 Publication History

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Estrada TFuentes OTaufer M(2008)A distributed evolutionary method to design scheduling policies for volunteer computingACM SIGMETRICS Performance Evaluation Review10.1145/1481506.148151536:3(40-49)Online publication date: 30-Nov-2008
https://dl.acm.org/doi/10.1145/1481506.1481515
Estrada TFuentes OTaufer MRamirez ABiliardi GGschwind M(2008)A distributed evolutionary method to design scheduling policies for volunteer computingProceedings of the 5th conference on Computing frontiers10.1145/1366230.1366282(313-322)Online publication date: 5-May-2008
https://dl.acm.org/doi/10.1145/1366230.1366282

Adapting convergent scheduling using machine learning (citation_only)
1. Computing methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
    2. Online algorithms
      1. Online learning algorithms
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning

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Published In

PPoPP '03: Proceedings of the ninth ACM SIGPLAN symposium on Principles and practice of parallel programming

June 2003

250 pages

ISBN:1581135882

DOI:10.1145/781498

General Chair:
Rudolf Eigenmann
Purdue University
,
Program Chair:
Martin Rinard
MIT Laboratory for Computer Science

ACM SIGPLAN Notices Volume 38, Issue 10
Proceedings of the ACM SIGPLAN symposium on principles and practice of parallel programming (PPoPP 2003) and workshop on partial evaluation and semantics-based program manipulation (PEPM 2003)
October 2003
331 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/966049
Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 11 June 2003

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PPoPP03: ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

June 11 - 13, 2003

California, San Diego, USA

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PPoPP '03 Paper Acceptance Rate 20 of 45 submissions, 44%;

Overall Acceptance Rate 230 of 1,014 submissions, 23%

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Estrada TFuentes OTaufer M(2008)A distributed evolutionary method to design scheduling policies for volunteer computingACM SIGMETRICS Performance Evaluation Review10.1145/1481506.148151536:3(40-49)Online publication date: 30-Nov-2008
https://dl.acm.org/doi/10.1145/1481506.1481515
Estrada TFuentes OTaufer MRamirez ABiliardi GGschwind M(2008)A distributed evolutionary method to design scheduling policies for volunteer computingProceedings of the 5th conference on Computing frontiers10.1145/1366230.1366282(313-322)Online publication date: 5-May-2008
https://dl.acm.org/doi/10.1145/1366230.1366282

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Single machine scheduling models with deterioration and learning: handling precedence constraints via priority generation

Single machine parallel-batch scheduling with deteriorating jobs

Single-machine scheduling with general learning functions

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Single machine scheduling models with deterioration and learning: handling precedence constraints via priority generation

Single machine parallel-batch scheduling with deteriorating jobs

Single-machine scheduling with general learning functions

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