Visiting Student - MCS - Gao, Yuhao - 2.2.26.

High-performance GPU compressors have been developed and optimized primarily for NVIDIA GPUs, but many are not easily portable to other GPU architectures. This limits their applicability on heterogeneous platforms, including those used in U.S. exascale supercomputers. This project aims to design and implement architecture-agnostic GPU compression techniques that achieve performance portability across major GPU ecosystems (e.g., NVIDIA, AMD, and Intel), enabling broader adoption in large-scale scientific computing and AI workloads.

Education and Experience Requirements

•   The entirety of the appointment must be conducted within the United States. 

•   Must be 18 years or older at the time the appointment begins.

•   Applicants must be:

• Currently enrolled in undergraduate or graduate studies at an accredited institution. 
• Graduated from an accredited institution within the past 3 months; or
• Actively enrolled in a graduate program at an accredited institution. 

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As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.