publication . Other literature type . Article . Part of book or chapter of book . 2018

Diagnosing Highly-Parallel OpenMP Programs with Aggregated Grain Graphs

Ananya Muddukrishna; Nico Reissmann;
Open Access
  • Published: 01 Jan 2018
  • Publisher: Springer International Publishing
  • Country: Norway
Abstract
Grain graphs simplify OpenMP performance analysis by visualizing performance problems from a fork-join perspective that is familiar to programmers. However, when programmers decide to expose a high amount of parallelism by creating thousands of task and parallel for-loop chunk instances, the resulting grain graph becomes large and tedious to understand. We present an aggregation method that hierarchically groups related nodes together to reduce grain graphs of any size to one single node. This aggregated graph is then navigated by progressively uncovering groups and following visual clues that guide programmers towards problems while hiding non-problematic regio...
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doi: 10.1007/978-3-319-96983-1_8
handle: 11250/2560809
Subjects
free text keywords: Theoretical computer science, Graph, Single node, Computer science
Related Organizations
Funded by
EC| TULIPP
Project
TULIPP
Towards Ubiquitous Low-power Image Processing Platforms
  • Funder: European Commission (EC)
  • Project Code: 688403
  • Funding stream: H2020 | IA
, EC| READEX
Project
READEX
Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing
  • Funder: European Commission (EC)
  • Project Code: 671657
  • Funding stream: H2020 | RIA
Communities
FET H2020FET HPC: HPC Core Technologies, Programming Environments and Algorithms for Extreme Parallelism and Extreme Data Applications
FET H2020FET HPC: Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing
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Part of book or chapter of book . 2018
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Other literature type . 2018
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