We are delighted to announce the latest NAG Library is available to download. Mark 27 brings extensive new functionality including Second-order Cone Programming, Derivative-free Optimization, First-order Active-set plus Non-negative Matrix Factorization, Nearest Correlation additions and more Adjoint versions of NAG solvers - learn more here.
Over the next few issues of NAGnews we will be highlighting the new functionality starting with Second-order Cone Programming (SOCP). This new solver is based on interior point method. It has become an important tool in many fields, ranging from engineering to control theory and quantitative finance, due to the wide range of applications and convex problems that it can solve, such as quadratically constrained quadratic problems (QCQP), robust linear programming and many others.
Learn more about NAG's SOCP and check out the examples for Portfolio Optimization using SOCP from Python on NAG's GitHub here - free trials of the new NAG Library are available.
We recommend that users move to the latest NAG Library because of additional functionality and guaranteed support levels (all supported clients are guaranteed technical assistance on the current release and one previous). If you have any questions about this release do contact your Account Manager or the NAG Technical Support Service.
Here at NAG we're excited about the latest version of the NAG Library, Mark 27, which is available now. As usual, it's involved an immense amount of effort from NAG staff, both development and commercial, and we've listened to many great ideas from our users and implemented them in the new Mark. For a full list of exciting new functionality click here.
User Benefits:
- At Mark 27 the NAG Library for C, Fortran and Algorithmic Differentiation are unified - on the NAG website you will see unified product downloads and documentation
- For Linux versions of the NAG Library, we now have "nagvars" shell scripts which will set up environment variables that help you get correct compile and link command lines
- The selection of the correct NAG Library becomes simpler because we now package C/C++, Fortran, 32-bit integer and 64-bit integer versions together in one package
Internally, NAG's development team have been calling this new Mark the "Unified Library". Why? Traditionally, we have produced a Fortran Library, a C/C++ Library, and wrapper code in various other languages which allow use of these compiled libraries in other environments. To cater for as many people as possible, we built variants with different integer sizes (32-bit or 64-bit) as well as using different compilers.
- Computing CVA and sensitivities using Origami and AD offers significant performance benefits compared with using finite differences and legacy grid execution software which might take many hours.
NAG has developed, in collaboration with Xi-FINTIQ, a CVA demonstration code to show how the NAG Library and NAG Algorithmic Differentiation (AD) tool dco/c++ combined with Origami - a Grid/Cloud Task Execution Framework available through NAG - can work together to solve large scale CVA computations.
CVA Demonstrator
Origami is a lightweight task execution framework. Users combine tasks into a task graph that Origami can execute on an ad-hoc cluster of workstations, on a dedicated in-house grid, on production cloud, or on a hybrid of all these. Origami handles all data transfers.
In our CVA demonstrator the trades in netting sets are valued in batches. CVA is calculated per netting set by running the code forward as normal. The graph is then reserved and the dco/c++ adjoint version of each task is run to calculate sensitivities with respect to market instruments. The resulting graph has a large number of tasks with non-trivial dependencies which Origami automatically processes and executes.
In July 2019 NAG's Mawussi Zounon presented three NAG Prizes to Manchester University students for their outstanding performance on the Numerical Analysis Undergraduate Study Pathway.
The winning students were: Yifan Yu, Benjamin Collard and Konstantin Siroki. Congratulations and well done to all of you!
NAG Numerical Software Developer & KTP Associate Mawussi Zounon presents Yifan Yu and Benjamin Collard with their awards - sadly we do not have a photo of Konstantin Siroki.
POP Webinar: Implementing I/O Best Practices to Improve System Performance with Ellexus
9 September 2019
CppCon 2019
Colorado, 15-20 September 2019
4th Conference on Research Software Engineers (RSE)
University of Birmingham, 17-19 September 2019
The Trading Show
New York, 25 September 2019
Fortran Modernization Workshop
TU Darmstadt, 25-26 September 2019
4th EAGE Workshop on HPC for Upstream
Dubai, 7-9 October 2019
The 15th WBS Quantitative Finance Conference
Rome, 16-18 October 2019
The Trading Show Europe
London, 17 October 2019
Quant Insights
London, 15 November 2019
SC19
Denver, 17-19 November 2019
My Student Placement Year at NAG
I'm Joe Davison, a Computer Science undergrad at Bath Uni, and I've just spent my year in industry at NAG as a Software Engineer. Working with NAG has been a brilliant opportunity to work in different areas of a software company, with support from experienced and super helpful colleagues.
