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Efficient AI Through Specialization

Series: Department Seminar

Speaker: Dr. Sanchari Sen, IBM TJ Watson Research Center, USA

Date/Time: Jan 06 10:00:00

Location: CSA Auditorium, (Room No. 104, Ground Floor)

Abstract:
Artificial Intelligence (AI) models have undergone tremendous improvements over the past decade and are now widely deployed in a range of products and services involving generation and analysis of image, video, speech and text. However, the immense compute, memory and energy demands of these AI models pose challenges to their more sustainable use and deployment. In this talk, I will discuss hardware-software specialization as a technique to overcome these challenges. Designing specialized hardware accelerators for AI has emerged as an attractive option to address the demands of AI workloads, resulting in numerous AI accelerators developed from both academia and industry. Extracting maximum benefits from an accelerator also requires designing a specialized software stack associated with it, to enable mapping of any AI workload to the accelerator. In this talk, I will discuss the details of IBM??s AIU Spyre accelerator and its software stack for improving the efficiency of AI model execution. I will specifically dive into the details of one component of the Spyre compiler that targets data-shuffle overheads in end-to-end AI acceleration.

Speaker Bio:
Sanchari Sen is a Staff Research Scientist at IBM T. J. Watson Research Center, Yorktown Heights, New York, USA, where she has been working since 2020. She received the B. Tech degree in Electronics and Electrical Communication Engineering from IIT Kharagpur, India and the PhD degree in Electrical and Computer Engineering from Purdue University, West Lafayette, Indiana, USA. Previously, she has interned with AMD Research, Austin, Texas and IBM T. J. Watson Research Center, Yorktown Heights, New York, USA. Her current research interests include hardware and software techniques for efficient deep learning, domain-specific accelerator designs and approximate computing. She has authored over 25 papers in top-tier conferences and journals on machine learning, design automation and computer architecture. She also holds several US patents related to efficient deep learning on different hardware platforms. She has received three Outstanding Research Division Achievement Awards and an Outstanding Technical Achievement Award from IBM Research. She was a recipient of the Ross Fellowship award in 2015 and the Bilsland Dissertation Fellowship in 2019 from Purdue University. She was also awarded the Institute Silver medal in 2011 for her academic performance at IIT Kharagpur.

Host Faculty: R Govindarajan