Part of the TPC Seminar Series

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Abstract:

With the new era of AIGC and large-scale language models being applied to change the landscape of the scientific discovery, DeepSpeed@Microsoft is establishing a new initiative with our partners from industry, academia and federal research labs to enable new science-driven system technologies to support large-scale science discovery through ML-driven models. In this talk, I will cover several of our signature models and engagements from our first release of DeepSpeed4Science and discuss what DeepSpeed system technologies are coming for the near future. DeepSpeed4Science is ultimately going to become a marketplace for scientists around the world to quickly acquire the essential system technologies that bottleneck their model development/deployment and also contribute to this new initiative. 

Biography:

Shuaiwen Leon Song is a senior principal scientist and manager at Microsoft. He is the chief scientist for Deepspeed4Science initiative which creates a broad engagement between Microsoft, Microsoft research, DoE labs, academia and industry partners to enable sophisticated system technology research and development for supporting aspects of training and inference for large-scale AI-driven scientific models. At DeepSpeed, he also drives or co-drives several pathfinding projects and releases (e.g., ZeRO inference, scalable dialogue system design and DeepSpeed Chat) and co-manages the Brainwave team.  Prior to Microsoft, he was the SOAR associate professor at University of Sydney and an adjunct professor at University of Washington.  His past works in HPC have received several best paper nominations and were featured in U.S. DoE research highlights and other media outlets. He was the recipient of several awards including IEEE early-career award for HPC, IEEE mid-career award for scalable computing, Facebook faculty award, Google brain faculty award, Australian most innovative engineer award, AIR global faculty award. He is also an ACM distinguished speaker.