TY - GEN
T1 - Relating memory performance data to application domain data using an integration API
AU - Husain, Benafsh
AU - Giménez, Alfredo
AU - Levine, Joshua A.
AU - Gamblin, Todd
AU - Bremer, Peer Timo
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under Grant No. IIS-1314757. This work was also performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory (LLNL-PROC-678035).
Publisher Copyright:
© 2015 ACM.
PY - 2015/11/15
Y1 - 2015/11/15
N2 - Understanding performance data, and more specifically memory access pattern is essential in optimizing scientific applications. Among the various factors affecting performance, such as the hardware architecture, the algorithms, or the system software stack, performance is also often related to the applications' physics. While there exists a number of techniques to collect relevant performance metrics, such as number of cache misses, traditional tools almost exclusively present this data relative to the code or as abstract tuples. This can obscure the data dependent nature of performance bottlenecks and make root-cause analysis difficult. Here we take advantage of the fact that a large class of applications are defined over some domain discretized by a mesh. By projecting the performance data directly onto these meshes, we enable developers to explore the performance data in the context of their application resulting in more intuitive visualizations. We introduce a lightweight, general interface to couple a performance visualization tool, MemAxes, to an external visualization tool, Visit. This allows us to harness the advanced analytic capabilities of MemAxes to drive the exploration while exploiting the capabilities of Visit to visualize both application and performance data in the application domain.
AB - Understanding performance data, and more specifically memory access pattern is essential in optimizing scientific applications. Among the various factors affecting performance, such as the hardware architecture, the algorithms, or the system software stack, performance is also often related to the applications' physics. While there exists a number of techniques to collect relevant performance metrics, such as number of cache misses, traditional tools almost exclusively present this data relative to the code or as abstract tuples. This can obscure the data dependent nature of performance bottlenecks and make root-cause analysis difficult. Here we take advantage of the fact that a large class of applications are defined over some domain discretized by a mesh. By projecting the performance data directly onto these meshes, we enable developers to explore the performance data in the context of their application resulting in more intuitive visualizations. We introduce a lightweight, general interface to couple a performance visualization tool, MemAxes, to an external visualization tool, Visit. This allows us to harness the advanced analytic capabilities of MemAxes to drive the exploration while exploiting the capabilities of Visit to visualize both application and performance data in the application domain.
UR - http://www.scopus.com/inward/record.url?scp=84960942536&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84960942536&partnerID=8YFLogxK
U2 - 10.1145/2835238.2835243
DO - 10.1145/2835238.2835243
M3 - Conference contribution
AN - SCOPUS:84960942536
T3 - Proceedings of VPA 2015: 2nd Workshop on Visual Performance Analysis - Held in conjunction with SC 2015: The International Conference for High Performance Computing, Networking, Storage and Analysis
BT - Proceedings of VPA 2015
PB - Association for Computing Machinery, Inc
T2 - 2nd Workshop on Visual Performance Analysis, VPA 2015
Y2 - 20 November 2015
ER -