Invited Talk: Hybrid AI/HPC Approaches for Next Generation Multi-Trillion-Parameter Models
SessionWorkshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH'22)
DescriptionWe live in a world where large-scale systems for machine intelligence are increasingly being used to solve complex problems in scientific research. A convergence of machine learning model adoption alongside classical algorithms, purpose-built scale-out systems availability in the cloud and maturing software ecosystems is paving the way for an exponential increase in the size of ML models being deployed at scale by research institutions. Models with trillions of parameters are not too far out in the future. New hybrid systems combining both classical and AI approaches will be required to meet the needs of these large-scale algorithms.
In this session, Graphcore will reveal how Intelligence Processing Unit (IPU) systems, purpose built for AI and particularly well suited to hybrid AI/HPC workloads, have been designed to tackle these compute scale-out challenges. This technology allows researchers to start small and then seamlessly scale to tackle mega-models, preparing them for the multi-trillion-parameter model era.
In this session, Graphcore will reveal how Intelligence Processing Unit (IPU) systems, purpose built for AI and particularly well suited to hybrid AI/HPC workloads, have been designed to tackle these compute scale-out challenges. This technology allows researchers to start small and then seamlessly scale to tackle mega-models, preparing them for the multi-trillion-parameter model era.
Event Type
Workshop
TimeSunday, 13 November 20221:30pm - 2:15pm CST
LocationC146
W
Algorithms
Exascale Computing
Extreme Scale Computing
Heterogeneous Systems
Post-Moore Computing
Quantum Computing
Recorded
Presenter