Information
- Publication Type: Poster
- Workgroup(s)/Project(s): not specified
- Date: April 2016
- Event: 4th International Workshop on OpenCL (IWOCL '16)
- Location: Vienna, Austria
- Publisher: ACM
Abstract
The use of GPUs and the massively parallel computing paradigm have become wide-spread. We describe a framework for the interactive visualization and visual analysis of the run-time behavior of massively parallel programs, especially OpenCL kernels. This facilitates understanding a program's function and structure, finding the causes of possible slowdowns, locating program bugs, and interactively exploring and visually comparing different code variants in order to improve performance and correctness. Our approach enables very specific, user-centered analysis, both in terms of the recording of the run-time behavior and the visualization itself. Instead of having to manually write instrumented code to record data, simple code annotations tell the source-to-source compiler which code instrumentation to generate automatically. The visualization part of our framework then enables the interactive analysis of kernel run-time behavior in a way that can be very specific to a particular problem or optimization goal, such as analyzing the causes of memory bank conflicts or understanding an entire parallel algorithm.
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BibTeX
@misc{klein-2016-WCL,
title = "Towards Interactive Visual Exploration of Parallel Programs
using a Domain-Specific Language",
author = "Tobias Klein and Stefan Bruckner and Meister Eduard
Gr\"{o}ller and Markus Hadwiger and Peter Rautek",
year = "2016",
abstract = "The use of GPUs and the massively parallel computing
paradigm have become wide-spread. We describe a framework
for the interactive visualization and visual analysis of the
run-time behavior of massively parallel programs, especially
OpenCL kernels. This facilitates understanding a program's
function and structure, finding the causes of possible
slowdowns, locating program bugs, and interactively
exploring and visually comparing different code variants in
order to improve performance and correctness. Our approach
enables very specific, user-centered analysis, both in terms
of the recording of the run-time behavior and the
visualization itself. Instead of having to manually write
instrumented code to record data, simple code annotations
tell the source-to-source compiler which code
instrumentation to generate automatically. The visualization
part of our framework then enables the interactive analysis
of kernel run-time behavior in a way that can be very
specific to a particular problem or optimization goal, such
as analyzing the causes of memory bank conflicts or
understanding an entire parallel algorithm.",
month = apr,
event = "4th International Workshop on OpenCL (IWOCL '16)",
location = "Vienna, Austria",
publisher = "ACM",
note = "Poster presented at 4th International Workshop on OpenCL
(IWOCL '16) ()",
URL = "https://www.cg.tuwien.ac.at/research/publications/2016/klein-2016-WCL/",
}