Automatic vectorization for multi-party computation
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Authors
Sherman, Benjamin
Issue Date
2022-08
Type
Electronic thesis
Thesis
Thesis
Language
en_US
Keywords
Computer science
Alternative Title
Abstract
We introduce a new compiler for multi-party computation (MPC) which performs backend-independent optimizations over the MPC Source intermediate representation and outputs C++ code using the MOTION framework for MPC. We showcase a specific optimization: novel automatic vectorization over MPC Source. This optimization is shown to provide significant performance improvement in most benchmarks, and mitigations are suggested to detect and prevent cases where this optimization leads to a performance regression. Both circuit generation and evaluation time improves, and there is a consistent reduction in communication size and amount. We additionally compare results to hand-optimized MOTION code and find that there are only minor differences which can easily be overcome in future work.
Description
August 2022
School of Science
School of Science
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY