Methods and Tools for Performance Modeling, Measurement, Analysis, Evaluation, and Prediction
Our goal is to develop and evaluate methodologies for generating performance models for algorithms and applications running on high-performance computer platforms. These models will be used to evaluate the performance-sensitive components in HPC systems and to predict performance when changing problem or system parameters, and when porting to different platforms.
The candidate must have a broad background in computing; a strong knowledge of algorithms, numerical techniques, and computational methods; expertise in one or more scientific NASA applications (e.g., aeronautics, space and Earth sciences); and experience programming distributed memory parallel computers, using message-passing, or data parallel programming paradigms.
Location:
Ames Research Center
Moffet Field, California
Field of Science:Technology Development
Advisors:
Subhash Saini
Subhash.Saini@nasa.gov
650-604-4343
Applications with citizens from Designated Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control.
Eligibility is currently open to:
- U.S. Citizens;
- U.S. Lawful Permanent Residents (LPR);
- Foreign Nationals eligible for an Exchange Visitor J-1 visa status; and,
- Applicants for LPR, asylees, or refugees in the U.S. at the time of application with 1) a valid EAD card and 2) I-485 or I-589 forms in pending status
- Degree: Doctoral Degree.
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