Wednesday, 8 March 2017

The women that helped create NAG - International Women's Day 2017

On International Women’s Day 2017 we are proud to highlight three pivotal women that played important roles in forming the Numerical Algorithms Group (NAG). 

NAG has been producing numerical software for over 4 decades which is a remarkable achievement given how hardware and algorithms have evolved during this time. Back in 1970 four people got together: Brian Ford, Lecturer at the University of Nottingham (later to become NAG Founder Director); Joan Walsh, University Reader in Numerical Analysis at the University of Manchester and expert on Ordinary Differential Equations; Shirley Lill, Lecturer in Optimization at the University of Leeds; and Linda Hayes, knowledgeable in Numerical Linear Algebra, and Research Assistant of Professor Leslie Fox (Director of the University of Oxford Computing Laboratory and Professor of Numerical Analysis). 

At this historic meeting on the 13 May 1970, Joan, Shirley, Linda, and Brian discussed their institutions new ICL 1906A Computers and the distinct lack of numerical libraries on them. They agreed to collaborate and build the Nottingham (later Numerical) Algorithms Group Library that would be shared within their universities. The benefit of this collaborative approach would be the greater coverage of the numerical algorithm expertise across their combined groups. Hence the NAG Library was born and first released in December 1971.

The NAG Library has continued to grow and improve ever since and today is still very much a collaborative product with new contributors donating code at nearly every release. One of NAG’s latest “Code Contributors” is Dr Rebecca Killick, Lecturer at the University of Lancaster who donated her PELT algorithm to the NAG Library and encourages her students and team to release their code to NAG. 

Like most companies in STEM areas, NAG’s current gender diversity is not ideal. However, NAG has always been a supporter and encourager of women in technology, and is committed to improving diversity within the company. Today my colleagues step forward to support the ‘Be Bold for Change’ theme of International Women’s Day 2017, and are committed in encouraging girls into STEM subjects at school and higher education. We embrace gender diversity in our organisation and believe that a truly diverse workforce will help build better products and ultimately secure the organisation’s future. By joining with groups like Women in HPC and the Girl Geeks movement we hope to see an improvement both within our own team and in the wider community.


#BeBoldForChange
#IWD2017

Thursday, 23 February 2017

New Mathematical Optimization Collaboration with the University of Oxford

NAG has recently started an academic collaboration with the Centre for Doctoral Training in Industrially Focused Mathematical Modelling (InFoMM) at the University of Oxford. Lindon Roberts is the main researcher supervised by Coralia Cartis, Associate Professor in Numerical Optimization. NAG is a strong supporter of InFoMM, offering student projects, providing training courses and sitting on the Industrial Engagement Committee.
This project focuses on mathematical optimization where derivatives are not readily available, so called derivative-free optimization (DFO). It is not easy or even possible to evaluate derivatives of functions which appear in the optimization model and thus many well-established approaches in mathematical optimization might not be satisfactory. Moving to a derivative-free regime presents novel approaches for approximating the solution without computing or estimating derivatives. NAG added its first derivative-free solver to the NAG Library about five years ago. Since then this field has attracted significant academic attention, resulting in numerous advances.
NAG started the collaboration with Lindon, Coralia and the InFoMM CDT earlier this year when a mini-project was sponsored to investigate DFO for nonlinear least squares optimization, a problem which is very common in the calibration of models in finance and engineering. After successful completion, NAG received not only a review of state-of-the-art DFO software, but also a working solver which will be adopted into the Library in 2017. We believe it will be the first such commercial solver available to the public anywhere in the world.
The full Doctoral project will focus on several open problems in DFO such as performance for noisy problems and the curse of dimensionality for large-scale problems. NAG will assist throughout the project by providing technical expertise and guidance, and by collaborating closely with Lindon to integrate his research into the NAG Library, enabling smooth and timely commercialisation of his research.

Academic collaborations remain a core part of our business and help the adoption of cutting-edge research into the NAG Library. The optimization software in the Library is an important part of its value to our customers and Lindon’s research into new techniques for DFO will enhance this further. We look forward to the continuation of this research.