Authors:
Cong Xie
1
;
Wei Xu
2
;
Sungsoo Ha
2
;
Kevin Huck
3
;
Sameer Shende
3
;
Hubertus Van Dam
2
;
Kerstin Kleese Van Dam
2
and
Klaus Mueller
1
Affiliations:
1
Stony Brook University, United States
;
2
Computational Science Initiative, United States
;
3
University of Oregon, United States
Keyword(s):
Performance, Visualization, TAU, Scientific Workflow.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
Visual Data Analysis and Knowledge Discovery
;
Visualization Applications
;
Visualization Tools and Systems for Simulation and Modeling
Abstract:
In exascale scientific computing, it is essential to efficiently monitor, evaluate and improve performance.
Visualization and especially visual analytics are useful and inevitable techniques in the exascale computing
era to enable such a human-centered experience. In this ongoing work, we present a visual analytics framework
for performance evaluation of scientific workflows. Ultimately, we aim to solve two current challenges: the
capability to deal with workflows, and the scalability toward exascale scenario. On the way to achieve these
goals, in this work, we first incorporate TAU (Tuning and Analysis Utilities) instrumentation tool and improve
it to accommodate workflow measurements. Then we establish a web-based visualization framework, whose
back end handles data storage, query and aggregation, while front end presents the visualization and takes
user interaction. In order to support the scalability, a few level-of-detail mechanisms are developed. Finally, a
chemistry workflow u
se case is adopted to verify our methods.
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