Tuesday, 17 May 2016

Who are the Customers of NAG's Impartial Expert HPC Consulting?

One of the questions I get asked most often while out and about in the HPC community at conferences, or visiting (prospective) customers is: "Who are your HPC consulting customers?".

The simple answer to that is most prefer to remain confidential, because they see a competitive advantage from using our HPC advice or services.

There are a few we are very proud to be able to name. For example NAG has worked with EPSRC to provide the Computational Science and Engineering Support Service as part of the HECToR national supercomputing service, and to provide independent expert advice on the technology options and procurement for the UK's national academic supercomputers (HECToR and ARCHER).

We enjoyed working with our friends at Red Oak Consulting to support the KAUST Shaheen II supercomputer procurement recently - see our joint press release.

There have been others that we have been able to name over the years. But, who are the confidential customers? Well, obviously I'm not going to be too indiscreet, but I can give some clues.

The oil and gas sector is a huge consumer of HPC, with clear articulations of the business value of exploiting HPC. In this sector, we have several active customers, including some of the worlds biggest and best-known oil companies. We are providing advice or hands-on support for technology planning, procurements, HPC software engineering and performance enhancements, HPC user support, cloud migration, and some other things, including HPC software experts permanently based on customer sites.

Internally, I lump together manufacturing, aerospace, high-tech engineering, etc. into one sector. Here, we have multiple customers, from multi-national companies to focused teams. We are mostly providing either HPC software performance services or experience-based advice on HPC technology planning and service delivery, including cloud.

Other active sectors include government/public sector/HPC centres; technology/IT companies; and finance. Life/medical sciences has not traditionally been a big sector for our HPC consulting but we have a few customer conversations there and expect this to grow over time.

Interestingly, although most customers remain totally confidential, the rules for some mean that they can be acknowledged in-person to non-competitors if we have a business reason to do so.

However, I think I will have to fall back on our marketing statistics to show the full HPC consulting experience of the NAG and Red Oak team:
  • 40+ projects in HPC strategy, procurement, or technology advice;
  • Throughout the world - UK, Europe, North America, Asia, Australia, Middle East, ...;
  • We have helped with around $1bn of customer HPC projects;
  • We have worked in academia, government and industry.
So, why do private sector and public sector organisations bring us in to help, when they often have in-house HPC expertise? Because we have experience across a diverse set of HPC users, we have genuine HPC technical expertise, and we have guaranteed independence and impartiality. That combination of experience, technical expertise and impartiality has been proven to deliver real value, reduce risks and ensure a better outcome for HPC strategy, technology, procurement and software performance projects.

I hope I've given a hint of our HPC consulting activity without being too indiscreet (if the reader is frustrated at the lack of detail then I'm probably doing a good job of respecting our clients' confidentiality wishes.)

If you are interested in more, please find me at various HPC events (e.g., ISC16 in Frankfurt in June), or via twitter (@hpcnotes), or via the NAG team: www.nag.com/contact_us.asp.

Wednesday, 11 May 2016

Portfolio Credit Risk: New Technical Report

In the latest NAG technical report we examine the main theoretical aspects in some models used in Portfolio credit risk. We introduce the well-known Vasicek model, the large homogeneous portfolios or Vasicek distribution and their corresponding generalizations. An illustrative example considering factors following a logistic distribution is presented. Numerical experiments for several homogeneous portfolios are performed in order to compare these methods. Finally, we use the NAG Toolbox for MATLAB® for implementing prototypes of these models quickly.

We described the most widely used models for the calculation of default probabilities in portfolio credit risk. We introduced the Vasicek one-factor model and its generalization for factors following non Normal distributions. Similarly, we presented the large portfolio approximation method and we generated closed-form expressions for the so-called general loss distribution. In section 7 we provide code for the main routines used throughout this technical report. The code is not designed to be fast, but to serve as a guidance and point of departure for more elaborate implementations. Furthermore, the code can be easily extended to heterogeneous portfolios. As shown, only a few lines of code using the NAG Toolbox for MATLAB are required to implement the studied models, which makes it extraordinarily suitable for prototyping.

You can read the report here.