November, 2022
QuantMinds 2022
'Automatic IFT - a step to transition overnight risk to live risk - MatLogica' by Dmitri Goloubentsev As presented at QuantMinds 2022 in Barcelona. Based Based on "Automatic Implicit Function Theorem" by Dmitri Goloubentsev, Evgeny Lakshtanov, and Vladimir Piterbarg as published at Risk.NET and SSRN.
December 7, 2021
QuantMinds 2021
'AAD integration strategies for top performance and ease of use' by Dmitri Goloubentsev from MatLogica as presented at QuantMinds in Barcelona on 7th December 2021.
November 17, 2021
WBS 17th Edition
A recording from WBS 17th Edition with Dmitri Goloubentsev on "MatLogica's AADC use for American Monte Carlo Option Pricing - Presenting an approach to efficiently implement adjoint differentiation for Longstaff Schwartz"
June 4, 2021
SIAM Conference on Financial Mathematics and Engineering (FM21) “New HPC Paradigm for Object Oriented Languages”
Based on our results with QuantLib and ORE, we demonstrated how MatLogica’s library works and introduced the idea of integration complexity.
May 18, 2021
‘Coffee chat’ with Pete Baker (Intel).
Leaders from Intel, MatLogica, and Quantifi sat down to discuss how Intel Xeon Scalable processors and Intel Software help to improve the performance of financial models analyzing financial risks and to effectively detect fraud.
March 22, 2021
The Quantitative Finance Conference Spring Edition (online) “AAD Integration Strategies”
IIn this presentation, we introduced MatLogica’s approach to achieving top performance and demonstrated the implementation process on a well-known open-source quant library – QuantLib, yielding 150x performance improvement for xVA calculations on a single core.
February 12, 2021
C++ London. Supercharging HPC for Object Oriented Languages
Dmitri Goloubentsev introduced MatLogica’s technique for hugely boosting performance of repetitive calculations.
August 11, 2020
23rd European Workshop on Automatic Differentiation
The First Virtual, Worldwide Workshop on Automatic Differentiation.
November 15, 2019
Presented : Breaking the Primal Barrier, Quant Insights AI, Machine Learning and Risk, London
October 15, 2019