Acceleration of lattice models for pricing portfolios of fixed-income derivatives

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Standard

Acceleration of lattice models for pricing portfolios of fixed-income derivatives. / Pawlak, Wojciech Michal; Hlava, Marek; Metaksov, Martin; Oancea, Cosmin Eugen.

ARRAY 2021 - Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2021. red. / Tze Meng Low; Jeremy Gibbons. Association for Computing Machinery, Inc., 2021. s. 27-38 3464309.

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Harvard

Pawlak, WM, Hlava, M, Metaksov, M & Oancea, CE 2021, Acceleration of lattice models for pricing portfolios of fixed-income derivatives. i TM Low & J Gibbons (red), ARRAY 2021 - Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2021., 3464309, Association for Computing Machinery, Inc., s. 27-38, 7th ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming, ARRAY 2021, held in association with PLDI 2021, Virtual, Online, Canada, 21/06/2021. https://doi.org/10.1145/3460944.3464309

APA

Pawlak, W. M., Hlava, M., Metaksov, M., & Oancea, C. E. (2021). Acceleration of lattice models for pricing portfolios of fixed-income derivatives. I T. M. Low, & J. Gibbons (red.), ARRAY 2021 - Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2021 (s. 27-38). [3464309] Association for Computing Machinery, Inc.. https://doi.org/10.1145/3460944.3464309

Vancouver

Pawlak WM, Hlava M, Metaksov M, Oancea CE. Acceleration of lattice models for pricing portfolios of fixed-income derivatives. I Low TM, Gibbons J, red., ARRAY 2021 - Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2021. Association for Computing Machinery, Inc. 2021. s. 27-38. 3464309 https://doi.org/10.1145/3460944.3464309

Author

Pawlak, Wojciech Michal ; Hlava, Marek ; Metaksov, Martin ; Oancea, Cosmin Eugen. / Acceleration of lattice models for pricing portfolios of fixed-income derivatives. ARRAY 2021 - Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2021. red. / Tze Meng Low ; Jeremy Gibbons. Association for Computing Machinery, Inc., 2021. s. 27-38

Bibtex

@inproceedings{dd97c455e88e4fee9640b4864b43e36d,
title = "Acceleration of lattice models for pricing portfolios of fixed-income derivatives",
abstract = "This paper reports on the acceleration of a standard, lattice-based numerical algorithm that is widely used in finance for pricing a class of fixed-income vanilla derivatives. We start with a high-level algorithmic specification, exhibiting irregular nested parallelism, which is challenging to map efficiently to GPU hardware. From it we systematically derive and optimize two CUDA implementations, which utilize only the outer or all levels of parallelism, respectively. A detailed evaluation demonstrates (i) the high impact of the proposed optimizations, (ii) the complementary strength and weaknesses of the two GPU versions, and that (iii) they are on average 2.4× faster than our well-tuned CPU-parallel implementation (OpenMP+AVX2) running on 104 hardware threads, and by 3-to-4 order of magnitude faster than an OpenMP-parallel implementation using the popular QuantLib library. ",
keywords = "Compilers, Computational Finance, Derivative Pricing, GPGPU (Parallel) Programming",
author = "Pawlak, {Wojciech Michal} and Marek Hlava and Martin Metaksov and Oancea, {Cosmin Eugen}",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 7th ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming, ARRAY 2021, held in association with PLDI 2021 ; Conference date: 21-06-2021",
year = "2021",
doi = "10.1145/3460944.3464309",
language = "English",
pages = "27--38",
editor = "Low, {Tze Meng} and Jeremy Gibbons",
booktitle = "ARRAY 2021 - Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2021",
publisher = "Association for Computing Machinery, Inc.",

}

RIS

TY - GEN

T1 - Acceleration of lattice models for pricing portfolios of fixed-income derivatives

AU - Pawlak, Wojciech Michal

AU - Hlava, Marek

AU - Metaksov, Martin

AU - Oancea, Cosmin Eugen

N1 - Publisher Copyright: © 2021 ACM.

PY - 2021

Y1 - 2021

N2 - This paper reports on the acceleration of a standard, lattice-based numerical algorithm that is widely used in finance for pricing a class of fixed-income vanilla derivatives. We start with a high-level algorithmic specification, exhibiting irregular nested parallelism, which is challenging to map efficiently to GPU hardware. From it we systematically derive and optimize two CUDA implementations, which utilize only the outer or all levels of parallelism, respectively. A detailed evaluation demonstrates (i) the high impact of the proposed optimizations, (ii) the complementary strength and weaknesses of the two GPU versions, and that (iii) they are on average 2.4× faster than our well-tuned CPU-parallel implementation (OpenMP+AVX2) running on 104 hardware threads, and by 3-to-4 order of magnitude faster than an OpenMP-parallel implementation using the popular QuantLib library.

AB - This paper reports on the acceleration of a standard, lattice-based numerical algorithm that is widely used in finance for pricing a class of fixed-income vanilla derivatives. We start with a high-level algorithmic specification, exhibiting irregular nested parallelism, which is challenging to map efficiently to GPU hardware. From it we systematically derive and optimize two CUDA implementations, which utilize only the outer or all levels of parallelism, respectively. A detailed evaluation demonstrates (i) the high impact of the proposed optimizations, (ii) the complementary strength and weaknesses of the two GPU versions, and that (iii) they are on average 2.4× faster than our well-tuned CPU-parallel implementation (OpenMP+AVX2) running on 104 hardware threads, and by 3-to-4 order of magnitude faster than an OpenMP-parallel implementation using the popular QuantLib library.

KW - Compilers

KW - Computational Finance

KW - Derivative Pricing

KW - GPGPU (Parallel) Programming

U2 - 10.1145/3460944.3464309

DO - 10.1145/3460944.3464309

M3 - Article in proceedings

AN - SCOPUS:85109009544

SP - 27

EP - 38

BT - ARRAY 2021 - Proceedings of the 7th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2021

A2 - Low, Tze Meng

A2 - Gibbons, Jeremy

PB - Association for Computing Machinery, Inc.

T2 - 7th ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming, ARRAY 2021, held in association with PLDI 2021

Y2 - 21 June 2021

ER -

ID: 306899886