The Convergence of Machine Learning and HPC for Cognitive Simulation

HPC managers are increasingly recognizing AI and Machine Learning’s ability to accelerate computing, extract more information out of data collected, and improve accuracy.

In this webinar, Brian Van Essen, Group Leader at Lawrence Livermore National Lab's Center for Applied Scientific Computing recently discusses advances in emerging workflows for HPC scientific exploration and scientific machine learning with Kisaco Research.

Viewers will gain insights into:

• Hybrid system results in accelerating multiple workloads
• Benefits of a highly programable architecture allowing multiple models to be laid out on a chip
• The ability of multiple model deployments to be programmed to handle each incoming request with production-ready efficiency
• Learnings from the first of its kind Disaggregated CogSim system and how it was built