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Multi-Party Computing for Privacy in Machine Learning Systems

Series: Department Seminar

Speaker: Prof. Murali Annavaram, Smt.Rukmini-Sri.Gopalakrishnachar Visiting Chair Professor, CSA, IISc & Univ. of Southern California, Los Angeles, CA, USA

Date/Time: Nov 25 11:00:00

Location: CSA Seminar Hall (Room No. 254, First Floor)

Faculty Advisor:

Given the resource management benefits such as elasticity, availability, and cost-effectiveness offered by cloud service providers, a growing number of machine learning workloads are migrated to the cloud for operations. Under this modern compute paradigm, confidential data and models can be leaked to unwanted parties if the service providers are curious, malicious, or compromised. The privacy concern is particularly pressing for natural language processing (NLP) where user’s audio features are inputs to ML models. These inputs contain sensitive private information about the users and require rigorous protection. Secure multi party computing (MPC) is one approach to tackle the privacy leaks without relying on any additional hardware support. MPC protocols provide strong security even when a subset of parties are compromised. However, when it comes to protecting privacy there is no free lunch, and in fact we show that it is a very expensive lunch. Through a detailed characterization of industry-strength MPC implementation of Transformer-based NLP models, we analyze where the MPC performance bottlenecks are. First, we show that Transformers rely extensively on softmax
Talk link

Speaker Bio:
Murali Annavaram is a Dean’s Chair Professor in the Ming-Hsieh Department of Electrical and Computer Engineering, and in the department of Computer Science (joint appointment) at the University of Southern California. He currently holds the Rukmini Gopalakrishnachar Visiting Chair Professorship at the Indian Institute of Science, Benguluru. He is the founding director of the REAL@USC-Meta center that is focused on research and education in AI and learning, and the co-PI on the DISCoVER NSF Expeditions center focused on superconducting technologies. His research group tackles a wide range of computer system design challenges, relating to energy efficiency, security and privacy. He has been inducted to the hall of fame for three of the prestigious computer architecture conferences ISCA, MICRO and HPCA. He served as the Technical Program Chair for HPCA 2021, and served as the General Co-Chair for ISCA 2018, and the Computer Architecture Track Chair for HiPC-2016 and SBACPAD-22 conferences. Prior to his appointment at USC he worked at Intel Microprocessor Research Labs from 2001 to 2007. His work at Intel lead to the first 3D microarchitecture paper, and also influenced Intel’s TurboBoost technology. In 2007 he was a visiting researcher at the Nokia Research Center working on mobile phone-based wireless traffic sensing using virtual trip lines, which later become Nokia Traffic Works product. In 2020 he was a visiting faculty scientist at Facebook, where he designed the checkpoint systems for distributed training. Murali co-authored Parallel Computer Organization and Design, a widely used textbook to teach both the basic and advanced principles of computer architecture. Murali received the Ph.D. degree in Computer Engineering from the University of Michigan, Ann Arbor, in 2001. He is a Fellow of IEEE and Senior Member of ACM.

Host Faculty: R Govindarajan