Data Parallel Accelerator Performance Intern
1 day ago
Requirements - Knowledge in one or more of the following areas, computer architecture , performance modeling, and analytical model - Knowledge and experience with common LLM (Large Language Model) workloads. - Proficiency in C or C++, and scripting languages such as Python. - Experience with high-level simulators for performance or power estimation is a plus. - Knowledge in server-class GPU/ML architecture is a plus.
Responsibilities - Responsible for an analytical model implementation of LLM inference and training memory usage - Responsible for running the performance simulation to extract the workload's characteristics such as memory footprint and bandwidth requirement. - Responsible for evaluation ideas for performance improvement
Minimum Education & Experience Current EE or CS master or Ph.D students with computer architecture backgrounds We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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