Sampling optimized code for type feedback
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00347259" target="_blank" >RIV/68407700:21240/20:00347259 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1145/3426422.3426984" target="_blank" >https://doi.org/10.1145/3426422.3426984</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3426422.3426984" target="_blank" >10.1145/3426422.3426984</a>
Alternative languages
Result language
angličtina
Original language name
Sampling optimized code for type feedback
Original language description
To efficiently execute dynamically typed languages, many language implementations have adopted a two-tier architecture. The first tier aims for low-latency startup times and collects dynamic profiles, such as the dynamic types of variables. The second tier provides high-throughput using an optimizing compiler that specializes code to the recorded type information. If the program behavior changes to the point that not previously seen types occur in specialized code, that specialized code becomes invalid, it is deoptimized, and control is transferred back to the first tier execution engine which will start specializing anew. However, if the program behavior becomes more specific, for instance, if a polymorphic variable becomes monomorphic, nothing changes. Once the program is running optimized code, there are no means to notice that an opportunity for optimization has been missed. We propose to employ a sampling-based profiler to monitor native code without any instrumentation. The absence of instrumentation means that when the profiler is not active, no overhead is incurred. We present an implementation is in the context of the A just-in-time, optimizing compiler for the R language. Based on the sampled profiles, we are able to detect when the native code produced by A is specialized for stale type feedback and recompile it to more type-specific code. We show that sampling adds an overhead of less than 3 2020 ACM.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000421" target="_blank" >EF15_003/0000421: Big Code: Scalable Analysis of Massive Code Bases</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
DSL_Proceedings of the 16th ACM SIGPLAN International Symposium on Dynamic Languages
ISBN
978-1-4503-8175-8
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
99-111
Publisher name
ACM
Place of publication
New York
Event location
virtual
Event date
Nov 15, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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