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Conference Papers Year : 2017

Sista: Saving Optimized Code in Snapshots for Fast Start-Up

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Abstract

Modern virtual machines for object-oriented languages such as Java HotSpot, Javascript V8 or Python PyPy reach high performance through just-in-time compilation techniques, involving on-the-fly optimization and deoptimization of the executed code. These techniques require a warm-up time for the virtual machine to collect information about the code it executes to be able to generate highly optimized code. This warm-up time required before reaching peak performance can be considerable and problematic. In this paper, we propose an approach, Sista (Speculative Inlining SmallTalk Architecture) to persist optimized code in a platform-independent representation as part of a snapshot. After explaining the overall approach, we show on a large set of benchmarks that the Sista virtual machine can reach peak performance almost immediately after start-up when using a snapshot where optimized code was persisted.
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Dates and versions

hal-01596321 , version 1 (27-09-2017)

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Cite

Clément Béra, Eliot Miranda, Tim Felgentreff, Marcus Denker, Stéphane Ducasse. Sista: Saving Optimized Code in Snapshots for Fast Start-Up. Proceedings of the 14th International Conference on Managed Languages and Runtimes, Sep 2017, Prague, Czech Republic. pp.1 - 11, ⟨10.1145/3132190.3132201⟩. ⟨hal-01596321⟩
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