Research Aide - LCF - Brembilla, Niccolò - 2.25.26.
About The Position
The objective of this project is to develop an integrated multi-knob performance-energy trade-off model for control of multiple knobs (node power limits, GPU/CPU/Uncore DVFS ...) in order to overcome the limitations of single knob approaches. This is done by establishing lightweight response models which describe how run time and energy vary based on different knob combinations at different phases of workload. These are then used to identify the best configuration based upon a combination of performance and facility power constraints. The model incorporates node-to-node variability, allowing a non-uniform system-wide power assignment, thereby improving load balancing and total system throughput. The effectiveness of the developed solution will be assessed with representative HPC and large-scale AI workloads.
Requirements
- The entirety of the appointment must be conducted within the United States.
- Applicants must be: o Currently enrolled in undergraduate or graduate studies at an accredited institution. o Graduated from an accredited institution within the past 3 months; or o Actively enrolled in a graduate program at an accredited institution.
- Must be 18 years or older at the time the appointment begins.
- Must possess a cumulative GPA of 3.0 on a 4.0 scale.
- If accepting an offer, candidates may be required to complete pre-employment drug testing based on appointment length. All students remain subject to applicable drug testing policies.
- Must complete a satisfactory background check.
Benefits
- comprehensive benefits are part of the total rewards package.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
