PhD Position in ML Accelerator Programming for HPC and Scientific Computing

ML accelerators offer exceptional performance and energy efficiency, yet their use beyond ML remains limited. Join us to develop methods and tools to make ML devices accessible and productive for Scientific and High-Performance Computing.

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The growing computational demands of Machine Learning (ML) have led to the rise of spatial devices explicitly designed for ML workloads, such as the Cerebras Wafer Scale Engine, AMD Versal AI Engine, and Tenstorrent Blackhole.

Although these accelerators can offer performance and efficiency gains to application domains beyond ML (e.g., computational sciences, big data analytics, graph processing), their potential in these areas remains unexplored. This is largely due to the lack of comprehensive software ecosystems, making them difficult for experts to use and inaccessible to domain scientists.

In this PhD project, you will help bridge this gap by demonstrating best practices and by developing programm...