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Performance Tools for Scientific Computing with MPI, OpenACC, and Workflows


Shodor > NCSI > XSEDE EMPOWER > XSEDE EMPOWER Positions > Performance Tools for Scientific Computing with MPI, OpenACC, and Workflows

Status
Completed
Mentor NameKaren L. Karavanic
Mentor's XSEDE Affiliationeducator, research allocation user, reviewer, NSF PI
Mentor Has Been in XSEDE Community4-5 years
Project TitlePerformance Tools for Scientific Computing with MPI, OpenACC, and Workflows
SummaryParticipate in PPerfLab research in developing performance tools for medium to large scale parallel programs. We are developing monitoring tools to provide useful feedback to developers to guide them in addressing performance issues in their code, particularly related to workflows and data movement.
Job DescriptionThis work will entail conducting experiments with MPI- and OpenACC-based codes, using a variety of tools to evaluate the runtime performance. The particular focus will be the data movement and storage, the underlying platform architectural features, and the relationship between the code and the resulting performance. The student will receive training in using a shared cluster environment, using the Lustre parallel file system, and using a variety of development tools. Also additional training for writing MPI and OpenACC - based codes. One application of focus will be a drought prediction code developed at Portland State in a collaborative research project.
Computational ResourcesThis project will use time on Linux clusters, on the PSU Coeus cluster, and on machines in the PI's laboratory. Our lab has only a small older 16-node Linux cluster with a "mini-Lustre" installation for initial learning. We hope to use Stampede or a similar XSEDE resource to allow the student to learn how to develop and run science codes at the medium scale.
Contribution to Community
Position TypeApprentice
Training PlanStudent must have programming skills in C/C++ in a Linux environment, and a basic understanding of MPI and multithreaded code. The student will step through a series of exercises to develop MPI codes and also to run the NAS parallel benchmarks, and to use the TAU tracing tools. The student will work with the PI and also graduate students.
Student Prerequisites/Conditions/QualificationsGood communication skills and ability to work effectively with people from all different cultures and of different education levels from high school students to Ph.D. students.
DurationSummer
Start Date06/22/2019
End Date08/30/2019

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