Optimal Scheduling of Contract Algorithms for Anytime Problem-Solving

Authors: A. Lopez-Ortiz, S. Angelopoulos, A. M. Hamel

JAIR 2014 | Venue PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper we give matching (i.e., optimal) upper and lower bounds for the acceleration ratio under such a simulation. We assume the most general setting in which n problem instances must be solved by means of scheduling executions of contract algorithms in m identical parallel processors. [...] In this section we prove a lower bound on the acceleration ratio which applies to all schedules.
Researcher Affiliation Academia Alejandro L opez-Ortiz EMAIL Cheriton School of Computer Science University of Waterloo Waterloo, Ontario, Canada, N2L 3G1. Spyros Angelopoulos EMAIL CNRS and Laboratoire d Informatique Universit e Pierre et Marie Curie 4 Place Jussieu 75252, France. Ang ele M. Hamel EMAIL Department of Physics and Computer Science Wilfrid Laurier University Waterloo, Ontario, Canada, N2L 3C5.
Pseudocode No The paper describes algorithms and scheduling strategies conceptually and mathematically, but it does not include any explicitly labeled pseudocode or algorithm blocks with structured steps.
Open Source Code No The paper does not contain any statement about releasing source code for the methodology described, nor does it provide links to code repositories or mention code in supplementary materials.
Open Datasets No This paper is theoretical, focusing on proving optimal bounds for scheduling algorithms. It does not describe or utilize any specific datasets for empirical evaluation.
Dataset Splits No The paper is theoretical and does not involve empirical evaluation on datasets, therefore there are no dataset splits described.
Hardware Specification No The paper is theoretical and does not describe any specific hardware used for running experiments. It refers to 'm identical parallel processors' as an abstract component of the problem definition rather than actual hardware.
Software Dependencies No The paper is theoretical and does not describe any specific software dependencies with version numbers used for implementation or analysis.
Experiment Setup No The paper is theoretical and focuses on mathematical proofs and analysis of scheduling algorithms. It does not detail a concrete experimental setup, including hyperparameters or system-level training settings.