Analyzing performance variation of task schedulers with TaskInsight

Author:

Ceballos GermánORCID,Grass Thomas,Hugo AndraORCID,Black-Schaffer David

Funder

Swedish Research Council

European Union’s Horizon 2020

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference16 articles.

1. Interactive visualization of cross-layer performance anomalies in dynamic task-parallel applications and systems;Drebes,2016

2. Para Prof: a portable, extensible, and scalable tool for parallel performance profile analysis;Bell,2003

3. Faithful performance prediction of a dynamic task-based runtime system for heterogeneous multi-core architectures;Stanisic;Concurr. Comput.,2015

4. Criticality-aware dynamic task scheduling for heterogeneous architectures;Chronaki,2015

5. Quantifying locality in the memory access patterns of HPC applications;Weinberg,2005

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1. Providing In-depth Performance Analysis for Heterogeneous Task-based Applications with StarVZ;2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW);2021-06

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