NAGnews 145

Posted on
12 Jan 2017

In this issue:


New Technical Report: Index-tracking Portfolio Optimization Model


Index-tracking is a form of passive fund management. The index-tracking problem is the problem of reproducing the performance of a stock market index by considering a portfolio of assets comprised on the index. This approach differs from the full replication strategy, where a fund purchases all the stocks that make up a particular market index. A passively managed fund whose objective is to reproduce the return on an index is known as an index fund, or a tracker fund. The classical index-tracking approach represents the problem in a least square framework with errors computed using a sample of historical data. A new approach described in N. C. P. Edirisinghe "Index-tracking optimal portfolio selection" Quantitative Finance Letters, Vol. 1, 16-20, (2013), which this report is based on, replaces the classical risk measure of portfolio variance by the variance of tracking errors between stochastic index return and the return on the portfolio selection. In this report we formulate the index-tracking portfolio optimization model and present an illustrative example where we compare the presented model with the classical Markowitz mean-variance portfolio optimization model.

You can read the report here.


NAG helps refactor an application to make use of HPC systems for pipeline simulations


ENGYS, a software company providing Computational Fluid Dynamics (CFD) solutions for engineering analysis and optimization identified the need to offer their users an enhanced solution that could exploit the power within High Performance Computing (HPC) platforms while still working optimally on non-HPC systems. Knowing that NAG understand the complexities of making applications run on HPC systems, ENGYS commissioned NAG to enhance their flagship CFD software, HELYX.

Key to the application enhancement of HELYX was the development of a client-server communication module to configure, submit and visualize CFD jobs as they run on a remote HPC platform. NAG helped the provision of real-time visualization capability to be embedded in HELYX by making use of ParaView and the Visualization Toolkit (VTK). Through this NAG established best practices for ENGYS and advised on the development of the visualization component to perform remote parallel rendering on large datasets, with options to use either software rendering or accelerator hardware.

In addition to the application enhancement, NAG also created a script-based solution to streamline the process of deploying the OpenFOAM environment, upon which HELYX is built, on most types of modern HPC systems to host simulations. This helped lower the technical barriers of using the popular open-source simulation package.


Simulation of flow over an oil & gas pipeline component

Read the case study in full here.


NAG Prize Winner Caitlin Chalk Best Performance MSc/PhD Fluid Dynamics, University of Leeds


NAG was delighted for Professor Peter Jimack, University of Leeds, and NAG Director, to present our latest NAG Prize to winner Caitlin Chalk recently.

The NAG Prize was awarded to the student who achieved the best performance on the MSc within the integrated MSc/PhD Fluid Dynamics programme in cohort one. Out of 12 students in cohort one, 10 achieved distinctions, with Caitlin achieving the highest overall mark. Caitlin is now undertaking a PhD project on Computational Fluid Dynamics Modelling of Debris Flow Runout, she has a background in Mathematics and studied her undergraduate at Leeds.

More information on cohort one (2014 cohort), their backgrounds and PhD projects is available here: http://www.fluid-dynamics.leeds.ac.uk/student-profiles/. Information about the programme is available on Leeds' website: http://www.fluid-dynamics.leeds.ac.uk/programme/.


Congratulations and well done Caitlin, from all at NAG!


NAG Library for Intel® Xeon Phi™ (Knights Landing) - latest version now available


NAG have recently released a version of the NAG C Library for users of the Intel® Xeon Phi™ 7200 Processor (Knights Landing), enabling the use of fast and efficient numerical algorithms for accurate computation on this hardware.

This new implementation of the Library is designed to run well on the Xeon Phi many core design, using SMP parallelism to provide improved performance at the numerical level - so your models or simulations that use the NAG Library should run better than ever!


Best of the Blog


Secrets, lies, women and money: the definitive summary of SC16

NAG's VP HPC Business, Andrew Jones, blogs about his time at the Supercomputing Conference held in November 2016.

Read his piece here.


Out & About with NAG


Come and see us at various conferences and events over the next few months.

Rice University Oil & Gas HPC Conference
15-16 March 2017

Fortran Modernization Workshop
24-26 July 2017