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Modifications to a classic BFGS library for use with SIMD-equipped hardware and an AAD library

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  • Evgeny Goncharov
  • Alexandre Rodrigues

Abstract

We introduce certain modifications of the BFGS method for functions that are not parallelizable by nature (having consecutive operations only) taking advantage of SIMD. We also provide a modified LBFGS\texttt{++} library that takes advantage of these modifications, and the use of AAD, and give an interface for AAD users that takes advantage of the modified library automatically. We give two examples to illustrate the performance. The modified library is up to 3.8 times faster for European Swaption curve calibration in ORE (not parallelizable) and 1.4 times faster for calibrating the LMM model by a set of European options.

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  • Evgeny Goncharov & Alexandre Rodrigues, 2022. "Modifications to a classic BFGS library for use with SIMD-equipped hardware and an AAD library," Papers 2209.14928, arXiv.org.
    • Handle: RePEc:arx:papers:2209.14928
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    References listed on IDEAS

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    1. Dmitri Goloubentsev & Evgeny Lakshtanov, 2019. "Remarks on stochastic automatic adjoint differentiation and financial models calibration," Papers 1901.04200, arXiv.org, revised Dec 2019.
    2. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    3. Jos'e Brito & Andrei Goloubentsev & Evgeny Goncharov, 2022. "Automatic Adjoint Differentiation for special functions involving expectations," Papers 2204.05204, arXiv.org, revised Jan 2023.
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