Accelerators for machine learning (focusing on supporting GNN-related algorithms)

Abstract

The use of advanced machine learning algorithms started having a tremendous impact on almost every aspect of our life. However, the ability to take advantage of these new capabilities heavily depends on the vast computation power it needs. A significant factor in providing the required computational resources is the ability to develop accelerators that fit the needs of such algorithms.

I will discuss the main differences between general-purpose processors and accelerators in my talk. Then, I will extend the discussion to machine learning accelerators in general and accelerators that support Graph Neural Networks.

A short Bio:

Avi Mendelson is a Professor at the CS department Technion and an IEEE Fellow. He has industrial and academic experience in various areas, such as Computer architecture, Hardware Security, Hardware accelerators, and Architecture for machine learning.

He graduated from the CS department, Technion, BSC (1979) and MSC (1982) and got his Ph.D. (1990) from the University of Massachusetts at Amherst (UMASS).

Among his industrial jobs, he worked for 11 years as a senior computer architect and principal engineer at Intel; he managed the academic-relations activities for Microsoft R&D Israel for four years, focusing on students’ innovation and research collaborations. In addition, he served as a PI in various EU projects, among them the EuroLab4HPC aiming at encouraging technology transfer between academia and startups.