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Multiresolution Analysis Using Data-Flow Programming

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Multiresolution analysis (MRA) is widely used across scientific disciplines for its ability to represent both local and global data features effectively. Representations in MRA are tree-based with levels corresponding to the scale at which the function is represented. The operations that construct these representations and act on them are irregular and data-dependent and require traversal of the tree. The Template Task Graph (TTG) programming model enables data-dependent task discovery and can represent large-scale task graphs compactly by instantiating only those tasks for which inputs are available. We introduce a framework that implements MRA using TTG. Our work explores the representation of functions, operators, and the application of operators on functions in a multiresolution multiwavelet basis. Our construction tackles a variety of feasibility, efficiency, and numerical challenges in higher dimensions.

Original languageEnglish
Title of host publicationAsynchronous Many-Task Systems and Applications - 4th International Workshop, WAMTA 2026, Proceedings
EditorsPatrick Diehl, Markus Rampp, Erwin Laure, Martin Schulz
PublisherSpringer Science and Business Media Deutschland GmbH
Pages151-160
Number of pages10
ISBN (Print)9783032276759
DOIs
StatePublished - 2026
Event4th International Workshop on Asynchronous Many-Task Systems and Applications, WAMTA 2026 - Hybrid, Garching, Germany
Duration: Feb 16 2026Feb 18 2026

Publication series

NameLecture Notes in Computer Science
Volume16592 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Workshop on Asynchronous Many-Task Systems and Applications, WAMTA 2026
Country/TerritoryGermany
CityHybrid, Garching
Period02/16/2602/18/26

Keywords

  • Data-Flow
  • Multiresolution Analysis
  • Task Based Programming
  • Template Task Graphs

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