Hardware Considerations for Accelerating Insights from Big Data

Capturing rapid and deeper insights from at-scale big Graph/unstructured data requires different hardware architectural thinking as compared to the traditional. Compute, memory and I/O or network considerations must be rebalanced keeping in mind the importance of latency in such architectures. This session will focus on considerations that must be paid to defining the hardware system architecture drawing parallels to Intel Programmable Integrated Unified Memory Architecture (PIUMA).
 

Nikhil M. Deshpande is the Director of AI / HPC Product Development in Data Platforms Group at Intel. He leads several advanced technology incubations and development in High Performance Compute, AI and Security. Nikhil has been invited speaker and panelist at numerous conferences and has 15+ US and international patents He holds M.S. and Ph.D. in Electrical and Computer Engineering from Portland State University. He also has M.S. in Technology Management from Oregon Graduate Institute.