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PLDI 2020
Mon 15 - Fri 19 June 2020

We show how to infer deterministic cache replacement policies using off-the-shelf automata learning and program synthesis techniques. For this, we construct and chain two abstractions that expose the cache replacement policy of any set in the cache hierarchy as a membership oracle to the learning algorithm, based on timing measurements on a silicon CPU. Our experiments demonstrate an advantage in scope and scalability over prior art and uncover two previously undocumented cache replacement policies.

Thu 18 Jun

Displayed time zone: Pacific Time (US & Canada) change

16:00 - 17:00
16:00
20m
Talk
Multi-modal Synthesis of Regular Expressions
PLDI Research Papers
Qiaochu Chen University of Texas at Austin, USA, Xinyu Wang University of Michigan at Ann Arbor, USA, Xi Ye University of Texas at Austin, USA, Greg Durrett University of Texas at Austin, USA, Işil Dillig University of Texas at Austin, USA
16:20
20m
Talk
Optimizing Homomorphic Evaluation Circuits by Program Synthesis and Term Rewriting
PLDI Research Papers
DongKwon Lee Seoul National University, South Korea, Woosuk Lee Hanyang University, South Korea, Hakjoo Oh Korea University, South Korea, Kwangkeun Yi Seoul National University, South Korea
16:40
20m
Talk
CacheQuery: Learning Replacement Policies from Hardware Caches
PLDI Research Papers
Pepe Vila IMDEA Software Institute, Spain, Pierre Ganty IMDEA Software Institute, Spain, Marco Guarnieri IMDEA Software Institute, Spain, Boris Köpf Microsoft Research, n.n.