Monday, April 22, 2019 - 4:00pm to 4:50pm
LINC 200

Speaker Information

Vikram Saletore
Principal Engineer
Artificial Intelligence Products Group
Intel Corp.
Hillsboro, Oregon


Driven by an exponential increase in the volume and diversity of data during the past 15 years, we have observed Data Analytics (DA) and High Performance Computing (HPC) workloads sharing the same infrastructure. We are witnessing another convergence taking place of Artificial Intelligence (AI) and HPC due to the rapid development and use of Deep Learning/Machine Learning frameworks and algorithms with scientific HPC applications. This convergence has begun to reshape the landscape of scientific computing and is enabling scientists address large problems in ways that were not possible before. I will also present how the software stacks are supported efficiently over a versatile general purpose computing architecture minimizing data movement saving time, energy, and costs. I will also present some of the challenges and opportunities with use cases on multiple collaborations with customers in Compute Service Provider (SURFsara), High Energy Physics (CERN), Healthcare (Novartis, Max Planck), and national research labs.

Speaker Bio

Vikram Saletore, a Principal Engineer with Artificial Intelligence Products Group, Intel Corp, leads a team for Deep Learning solutions and performance with customers. He collaborates with Enterprise/Government, HPC, & OEMs customers on Deep Learning Training and Inference. Vikram is also an Intel Parallel Computing Center Co-PI for deep learning research and collaboration with; SURFsara, CERN, Max Planck, & GENCI. Vikram has 25+ years of experience and delivered optimized software to Oracle & Informix parallel databases and worked on performance modeling for Intel CPU platforms and Data Center Optane™ memory technical readiness. As a Research Scientist with Intel Labs he led collaboration with HP Labs, Palo Alto on networking acceleration. Prior to Intel, as a faculty in Computer Science at OSU, Corvallis, OR, Vikram led NSF funded research in parallel and distributed computing supervising 8 students (1 PhD, 7 MS). He also developed CPU and Networking products at DEC and AMD. Vikram received his MS from Berkeley & PhD in EE in Parallel Computing from Univ. of Illinois at Urbana-Champaign. He has published 50+ peer-reviewed publications and 40+ white papers, and blogs and has multiple patents issued.