Faster Sorting Algorithm with Machine Learning
Organization
Scaling and Intelligence Lab (SaIL)
Abstract
Fundamental algorithms such as sorting or hashing are used trillions of times on any given day1. As demand for computation grows, it has become critical for these algorithms to be as performant as possible. Whereas remarkable progress has been achieved in the past2, making further improvements on the efficiency of these routines has proved challenging for both human scientists and computational approaches. Here we show how artificial intelligence can go beyond the current state of the art by discovering hitherto unknown routines. To realize this, we formulated the task of finding a better sorting routine as a single-player game. We then trained a new deep reinforcement learning agent, AlphaDev, to play this game. AlphaDev discovered small sorting algorithms from scratch that outperformed previously known human benchmarks. These algorithms have been integrated into the LLVM standard C++ sort library3. This change to this part of the sort library represents the replacement of a component with an algorithm that has been automatically discovered using reinforcement learning. We also present results in extra domains, showcasing the generality of the approach.
Main
Main
Graduation Theses defence year
2023-2024
Supervisor
Kallol Roy
Spoken language (s)
English
Requirements for candidates
Level
Bachelor, Masters
Keywords
Application of contact
Name
Kallol Roy
Phone
+37256051480
E-mail
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