On the Effects of Integrating Region-Based Memory Management and Generational Garbage Collection in ML

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

We present a region-based memory management scheme with support for generational garbage collection. The scheme is implemented in the MLKit Standard ML compiler, which features a compile-time region inference algorithm. The compiler generates native x64 machine code and deploys region types at runtime to avoid write barrier problems and to support partly tag-free garbage collection. We measure the characteristics of the scheme, for a number of benchmarks, and compare it to the Mlton state-of-the-art Standard ML compiler and configurations of the MLKit with and without region inference and generational garbage collection enabled. Although region inference often serves the purpose of generations, we demonstrate that, in some cases, generational garbage collection combined with region inference is beneficial.

OriginalsprogEngelsk
TitelPractical Aspects of Declarative Languages - 22nd International Symposium, PADL 2020, Proceedings
RedaktørerEkaterina Komendantskaya, Yanhong Annie Liu
Antal sider18
ForlagSpringer VS
Publikationsdato2020
Sider95-112
ISBN (Trykt)9783030391966
DOI
StatusUdgivet - 2020
Begivenhed22nd International Symposium on Practical Aspects of Declarative Languages, PADL 2020 - New Orleans, USA
Varighed: 20 jan. 202021 jan. 2020

Konference

Konference22nd International Symposium on Practical Aspects of Declarative Languages, PADL 2020
LandUSA
ByNew Orleans
Periode20/01/202021/01/2020
NavnLecture Notes in Computer Science
Vol/bind12007 LNCS
ISSN0302-9743

ID: 271602700