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Numerical Algorithms Group's Blog

Testing Matrix Function Algorithms Using Identities

April 10, 2014 Comments (0)

Edvin Deadman and Nick Higham (University of Manchester) write: In a previous blog post we explained how testing new algorithms is difficult. We discussed the forward error (how far from the actual solution are we?) and the backward error (what problem have we actually solved?) and how we'd like the backward error to be close to the unit roundoff, u. For matrix functions, we also mentioned the idea of using identities such as sin2A + cos2A = I to test algorithms. In...

The Wilkinson Prize for Numerical Software

March 21, 2014 Comments (0)

In honour of the outstanding contributions of James Hardy Wilkinson to the field of numerical software, Argonne National Laboratory, the National Physical Laboratory, and the Numerical Algorithms Group award the Wilkinson Prize for Numerical Software (US $3000). The 2015 prize will be awarded at the International Conference in Industrial and Applied Mathematics (ICIAM) in Beijing, China, August 2015. Entries must be received by July 1, 2014. Additional details on the Wilkinson Prize for...

C++ wrappers for the NAG C Library

February 6, 2014 Comments (0)

Motivation Occasionally, we recieve requests to make the NAG C Library easier to call from C++. In the past, we found it difficult to build something that would work across all of the code our C++ users write. With the advent of the C++11 standard, many of the key features of the widely used Boost library have been incorporated into the STL, and finally provide a standardized way to address many of the difficulties we've encountered (the code we describe here works with Visual Studios 2010 and...

Out and about this week – The London Thalesians Seminar

January 16, 2014 Comments (0)

NAG’s Brian Spector gave a great talk to a packed audience of finance professionals in London this week. The Thalesians describe themselves as a “think tank of dedicated professionals with an interest in quantitative finance, economics, mathematics, physics and computer science”. Brian was delighted to present "Implied Volatility using Pythons Pandas Library" at their recent London Seminar on Wednesday 15 January 2014.  Brian Spector presenting "Implied Volatility using Python's...

Using the NAG Compiler with the NAG Fortran Library (Mark 24) on Windows

November 28, 2013 Comments (0)

Blog written by David Sayers, NAG Principal Technical Consultant  Introduction The NAG Fortran Compiler is an excellent compiler for checking and running your Fortran code. We use it extensively here at NAG to ensure that our code for the library complies with the current Fortran standards. Personally whenever I have a user problem report that I can’t resolve by inspection my first instinct is to request run the users code with the Compiler. Frequently this identifies the error...

NAG at SC13

November 26, 2013 Comments (0)

A short summary of news from or about NAG at SC13. Quick fact: NAG is one of very few organizations that have been at every SC since the series started. Attacking the HPC skills need: NAG Supercomputing Support Service passes milestone of 2000 course attendees NAG announces the latest milestone in addressing the skills needs of the scientific computing community with the skills they require to effectively exploit HPC systems - over 2000 attendees have now benefitted from NAG's highly rated...

Implied Volatility using Python's Pandas Library

October 15, 2013 Comments (0)

Python has some nice packages such as numpy, scipy, and matplotlib for numerical computing and data visualization. Another package that deserves a mention that we have seen increasingly is Python's pandas library. Pandas has fast and efficient data analysis tools to store and process large amounts of data. Additionally, pandas has numpy and ctypes built into it which allow easy integration with NAG's nag4py package. Below is an example using nag4py and the pandas library to calculate the...

NAG Toolbox for MATLAB® documentation for the Mark 24 release

October 4, 2013 Comments (0)

A look at the documentation features in the new, Mark 24, release of the NAG Toolbox for MATLAB®. MATLAB Documentation Help Center Recent versions of MATLAB have a new documentation system known as the Help Center. This, however is restricted to products from MathWorks; third party extension toolboxes such as our NAG Toolbox for MATLAB® are now documented in a separate help application for Supplemental Software. This has necessitated changes in the way the NAG Toolbox documentation is...

How do I know I'm getting the right answer?

September 18, 2013 Comments (0)

Many recent developments in numerical algorithms concern improvements in performance and the exploitation of parallel architectures. However it's important not to lose sight of one crucial point: first and foremost, algorithms must be accurate. This begs the question, how do we know whether a routine is giving us the right answer? I'm asking this in the context of the matrix function routines I've been writing (these are found in chapter F01 of the NAG Library), but I'm sure you’ll agree that...

All the performance comes from parallel processing

August 30, 2013 Comments (0)

I often use this slide to show why all software has to be aware of parallel processing now. In short, if your software does not exploit parallel processing techniques, then your code is limited to less than 2% of the potential performance of the processor. And this is just for a single processor - it is even more critical if the code has to run on a cluster or a supercomputer. This is why NAG provides help to users and developers: training in parallel programming techniques; software...