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Virtual machine warmup blows hot and cold

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Virtual machine warmup blows hot and cold. / Barrett, Edd; Bolz-Tereick, Carl Friedrich; Killick, Rebecca et al.
In: Proceedings of the ACM on Programming Languages , Vol. 1, No. OOPSLA, 52, 01.10.2017.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Barrett, E, Bolz-Tereick, CF, Killick, R, Mount, S & Tratt, L 2017, 'Virtual machine warmup blows hot and cold', Proceedings of the ACM on Programming Languages , vol. 1, no. OOPSLA, 52. https://doi.org/10.1145/3133876

APA

Barrett, E., Bolz-Tereick, C. F., Killick, R., Mount, S., & Tratt, L. (2017). Virtual machine warmup blows hot and cold. Proceedings of the ACM on Programming Languages , 1(OOPSLA), Article 52. https://doi.org/10.1145/3133876

Vancouver

Barrett E, Bolz-Tereick CF, Killick R, Mount S, Tratt L. Virtual machine warmup blows hot and cold. Proceedings of the ACM on Programming Languages . 2017 Oct 1;1(OOPSLA):52. doi: 10.1145/3133876

Author

Barrett, Edd ; Bolz-Tereick, Carl Friedrich ; Killick, Rebecca et al. / Virtual machine warmup blows hot and cold. In: Proceedings of the ACM on Programming Languages . 2017 ; Vol. 1, No. OOPSLA.

Bibtex

@article{9ea0e1b365c444b38c21e270728a40d4,
title = "Virtual machine warmup blows hot and cold",
abstract = "Virtual Machines (VMs) with Just-In-Time (JIT) compilers are traditionally thought to execute programs in two phases: first the warmup phase determines which parts of a program would most benefit from dynamic compilation and JIT compiles them into machine code; after compilation has occurred, the program is said to be at peak performance. When measuring the performance of JIT compiling VMs, data collected during the warmup phase is generally discarded, placing the focus on peak performance. In this paper we first run a number of small, deterministic benchmarks on a variety of well known VMs, before introducing a rigorous statistical model for determining when warmup has occurred. Across 3 benchmarking machines only 43.3–56.5% of (VM, benchmark) pairs conform to the traditional view of warmup and none of the VMs consistently warms up.",
keywords = "changepoint, multivariate",
author = "Edd Barrett and Bolz-Tereick, {Carl Friedrich} and Rebecca Killick and Sarah Mount and Laurence Tratt",
year = "2017",
month = oct,
day = "1",
doi = "10.1145/3133876",
language = "English",
volume = "1",
journal = "Proceedings of the ACM on Programming Languages ",
issn = "2475-1421",
publisher = "ACM",
number = "OOPSLA",

}

RIS

TY - JOUR

T1 - Virtual machine warmup blows hot and cold

AU - Barrett, Edd

AU - Bolz-Tereick, Carl Friedrich

AU - Killick, Rebecca

AU - Mount, Sarah

AU - Tratt, Laurence

PY - 2017/10/1

Y1 - 2017/10/1

N2 - Virtual Machines (VMs) with Just-In-Time (JIT) compilers are traditionally thought to execute programs in two phases: first the warmup phase determines which parts of a program would most benefit from dynamic compilation and JIT compiles them into machine code; after compilation has occurred, the program is said to be at peak performance. When measuring the performance of JIT compiling VMs, data collected during the warmup phase is generally discarded, placing the focus on peak performance. In this paper we first run a number of small, deterministic benchmarks on a variety of well known VMs, before introducing a rigorous statistical model for determining when warmup has occurred. Across 3 benchmarking machines only 43.3–56.5% of (VM, benchmark) pairs conform to the traditional view of warmup and none of the VMs consistently warms up.

AB - Virtual Machines (VMs) with Just-In-Time (JIT) compilers are traditionally thought to execute programs in two phases: first the warmup phase determines which parts of a program would most benefit from dynamic compilation and JIT compiles them into machine code; after compilation has occurred, the program is said to be at peak performance. When measuring the performance of JIT compiling VMs, data collected during the warmup phase is generally discarded, placing the focus on peak performance. In this paper we first run a number of small, deterministic benchmarks on a variety of well known VMs, before introducing a rigorous statistical model for determining when warmup has occurred. Across 3 benchmarking machines only 43.3–56.5% of (VM, benchmark) pairs conform to the traditional view of warmup and none of the VMs consistently warms up.

KW - changepoint

KW - multivariate

U2 - 10.1145/3133876

DO - 10.1145/3133876

M3 - Journal article

VL - 1

JO - Proceedings of the ACM on Programming Languages

JF - Proceedings of the ACM on Programming Languages

SN - 2475-1421

IS - OOPSLA

M1 - 52

ER -