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FinPar: A Parallel Financial Benchmark

Authors:

Christian Andreetta,

Fritz Henglein,

Troels Henriksen,

Maj-Britt Nordfang,

Cosmin E. OanceaAuthors Info & Claims

ACM Transactions on Architecture and Code Optimization (TACO), Volume 13, Issue 2

Article No.: 18, Pages 1 - 27

https://doi.org/10.1145/2898354

Published: 27 June 2016 Publication History

Abstract

Commodity many-core hardware is now mainstream, but parallel programming models are still lagging behind in efficiently utilizing the application parallelism. There are (at least) two principal reasons for this. First, real-world programs often take the form of a deeply nested composition of parallel operators, but mapping the available parallelism to the hardware requires a set of transformations that are tedious to do by hand and beyond the capability of the common user. Second, the best optimization strategy, such as what to parallelize and what to efficiently sequentialize, is often sensitive to the input dataset and therefore requires multiple code versions that are optimized differently, which also raises maintainability problems.

This article presents three array-based applications from the financial domain that are suitable for gpgpu execution. Common benchmark-design practice has been to provide the same code for the sequential and parallel versions that are optimized for only one class of datasets. In comparison, we document (1) all available parallelism via nested map-reduce functional combinators, in a simple Haskell implementation that closely resembles the original code structure, (2) the invariants and code transformations that govern the main trade-offs of a data-sensitive optimization space, and (3) report target cpu and multiversion gpgpu code together with an evaluation that demonstrates optimization trade-offs and other difficulties. We believe that this work provides useful insight into the language constructs and compiler infrastructure capable of expressing and optimizing such applications, and we report in-progress work in this direction.

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Cited By

Schenck RHinnerskov NHenriksen TMadsen MElsman M(2024)AUTOMAP: Inferring Rank-Polymorphic Function Applications with Integer Linear ProgrammingProceedings of the ACM on Programming Languages10.1145/36897748:OOPSLA2(1787-1813)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689774
Munksgaard PHenriksen TSadayappan POancea CWolf FShende SCulhane CAlam SJagode H(2022)Memory optimizations in an array languageProceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis10.5555/3571885.3571926(1-15)Online publication date: 13-Nov-2022
https://dl.acm.org/doi/10.5555/3571885.3571926
El Kharroubi MCoudray BMalaspinas OHenriksen TLow T(2022)Distributed parallel computing with Futhark: a functional language to generate distributed parallel codeProceedings of the 8th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming10.1145/3520306.3534501(12-24)Online publication date: 13-Jun-2022
https://dl.acm.org/doi/10.1145/3520306.3534501
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Index Terms

FinPar: A Parallel Financial Benchmark
1. Computing methodologies
  1. Parallel computing methodologies
    1. Parallel programming languages
2. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Source code generation
  2. Software organization and properties
    1. Extra-functional properties
      1. Software performance

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cover image ACM Transactions on Architecture and Code Optimization

ACM Transactions on Architecture and Code Optimization Volume 13, Issue 2

June 2016

200 pages

ISSN:1544-3566

EISSN:1544-3973

DOI:10.1145/2952301

Editor:
Koen De Bosschere
Ghent University

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Copyright © 2016 ACM.

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Publication History

Published: 27 June 2016

Accepted: 01 February 2016

Revised: 01 February 2016

Received: 01 August 2015

Published in TACO Volume 13, Issue 2

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Schenck RHinnerskov NHenriksen TMadsen MElsman M(2024)AUTOMAP: Inferring Rank-Polymorphic Function Applications with Integer Linear ProgrammingProceedings of the ACM on Programming Languages10.1145/36897748:OOPSLA2(1787-1813)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689774
Munksgaard PHenriksen TSadayappan POancea CWolf FShende SCulhane CAlam SJagode H(2022)Memory optimizations in an array languageProceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis10.5555/3571885.3571926(1-15)Online publication date: 13-Nov-2022
https://dl.acm.org/doi/10.5555/3571885.3571926
El Kharroubi MCoudray BMalaspinas OHenriksen TLow T(2022)Distributed parallel computing with Futhark: a functional language to generate distributed parallel codeProceedings of the 8th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming10.1145/3520306.3534501(12-24)Online publication date: 13-Jun-2022
https://dl.acm.org/doi/10.1145/3520306.3534501
Munksgaard PHenriksen TSadayappan POancea C(2022)Memory Optimizations in an Array LanguageSC22: International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SC41404.2022.00036(1-15)Online publication date: Nov-2022
https://doi.org/10.1109/SC41404.2022.00036
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Pawlak WHlava MMetaksov MOancea CLow TGibbons J(2021)Acceleration of lattice models for pricing portfolios of fixed-income derivativesProceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming10.1145/3460944.3464309(27-38)Online publication date: 17-Jun-2021
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Henriksen T(2021)Bounds Checking on GPUInternational Journal of Parallel Programming10.1007/s10766-021-00703-449:6(761-775)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1007/s10766-021-00703-4
Munksgaard PBreddam SHenriksen TGieseke FOancea C(2021)Dataset Sensitive Autotuning of Multi-versioned Code Based on Monotonic PropertiesTrends in Functional Programming10.1007/978-3-030-83978-9_1(3-23)Online publication date: 23-Aug-2021
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Pawlak WElsman MOancea C(2019)A functional approach to accelerating Monte Carlo based american option pricingProceedings of the 31st Symposium on Implementation and Application of Functional Languages10.1145/3412932.3412937(1-12)Online publication date: 25-Sep-2019
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Elsman MHenriksen TSerup NGibbons J(2019)Data-parallel flattening by expansionProceedings of the 6th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming10.1145/3315454.3329955(14-24)Online publication date: 8-Jun-2019
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