Graphs for HPC and LLMs

We are joined by Maciej Besta, a senior researcher of sparse graph computations and large language models at the Scalable Parallel Computing Lab (SPCL). In this episode, we explore the intersection of graph theory and high-performance computing (HPC), Graph Neural Networks (GNNs) and LLMs.

Guest

Maciej Besta: Maciej Besta leads research on broad graph computations and large language models at the Scalable Parallel Computing Lab at ETH Zurich and the ETH Future Computing Lab; he also works on other aspects of the high-performance computing landscape, including interconnects, general sparse computing, and others. Maciej published more than 50 top conference and journal papers. He won, among others, the competition for the Best Student of Poland (2012), the first Google Fellowship in Parallel Computing (2013), the ACM/IEEE-CS High-Performance Computing Fellowship (2015), the IEEE TCSC Award for Excellence in Scalable Computing Early Career (2023), and the OlympusMons Award for contributions to scalable storage systems (2024). His doctoral dissertation on irregular computations received the ETH Medal for an outstanding doctoral thesis (2021), Honorable Mention from SPEC as a distinguished dissertation in performance measurement and analysis (2022), and awards from IEEE (2021) and ACM (2022) for the best doctoral dissertation worldwide in - respectively - scalable computing and high-performance computing. Maciej also received Best Paper awards and nominations at ACM/IEEE Supercomputing 2013, 2014, 2019 (for 2 different papers), 2022, and 2023 (for 2 different papers); at ACM HPDC 2015 and 2016, ACM Research Highlights 2018, and others. Finally, Maciej is supported by the Fellowship in The Explorers Club (2022) for his exploratory mountaineering and polar expeditions into the most hard-to-get and coldest mountain ranges and plateaus on the planet.