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HPC,AI and Machine unLearning using OpenPOWER/POWER systems
Open OnDemand: HPC for Everyone
By Dr Robert Settlage , Virginia Tech

Dr. Robert Settlage joined ARC as a Computational and Data Scientist in March 2016. He obtained his PhD in Chemistry from the University of Virginia in 1999 and a MS in Statistics from Virginia Tech in 2018. Dr. Settlage’s career has taken him in an out of industry and academia. He has worked in companies as large as Merck where he led an Automation Lab and Proteomics Informatics efforts and companies as small as 5 person startups. His research interests lie in all aspects of data analysis from visualization of the data to improving the compute performance. Most recently, he is co-PI in a grant to improve access and utilization of HPC resources through a combination of Open OnDemand and XDMoD. These tools both improve HPC access through familiar browser based tools and bring job performance metrics straight to users for code review.


X-ScaleAI for Distributed Deep Learning
By Devesh Sharma , SME

Devesh Sharma is a Subject matter expert and Technology Advisor In Collaboration with Dr. D.K. Panda and Object Automation to demonstrate capabilities of X-ScaleHPC and X-ScaleAI to end users. In his 16+ years of career as a software developer he spearheaded development of RDMA provider driver/libraries for Broadcom, Emulex and C-DAC. His work scope includes contributions to various use cases of RDMA viz MPIs, Storage, middleware provider libraries (Openucx). He has been an expert of MVAPICH2, MVAPICH2-GDR and its surrounding applications. Recently, he played a key role in using Broadcom's 200G/100G adaptors on HPC workloads and demonstrated it at MVAPICH2 Users Group (MUG-2020) held at Ohio State University, Columbus Ohio USA.

Machine UnLearning
By Dr Murari, NUS

Murari is a Postdoctoral research fellow in the School of Computing, National University of Singapore (NUS). His earlier works focused on developing deep learning models for vision applications.

May 19, 2022 07:00 PM in India

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