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GPUs, Monte Carlo Simulation and Kooderive with Professor Mark Joshi - February 25-27th, London, UK - Further Information
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Short Description: The Numerical Algorithms Group (NAG) delivers trusted, high quality numerical computing software and high performance computing (HPC) services

Address: Wilkinson House, Jordan Hill Road, OX2 8DR

City: Oxford

Country: UK

Telephone: +44 (0)1865 511245

Website: http://www.nag.co.uk/

Blog URL: link

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RSS Feed: link

Joined: June 8th, 2011

Activity

Numerical Algorithms Group wrote a new blog post titled Gaussian Mixture Model

With the release of Mark 24 of the NAG C Library comes a plethora of new functionality including matrix functions, pricing Heston options w/term structure, best subset selection, and element-wise weightings for the nearest correlation matrix. Among the new routines I was excited to test out was the Gaussian mixture model (g03ga).This routines will take a set of data points and fit a mixture of Gaussians for a given (co)variance structure by maximizing the log-likelihood function. The user inputs the (co)variance structure, number of groups, and (optionally) the initial membership...
(30 days ago)

Numerical Algorithms Group wrote a new blog post titled Secrets of HPC Procurement

Liked my article today in HPC Wire "Secrets of the Supercomputers"? I firmly poke fun at various elements of an imaginary supercomputer procurement process. However, I'm sure many readers will also see familiar and painfully serious aspects in the fictional story. As I mention at the bottom of that article, NAG can help make the process of buying HPC systems much better than the worrying case in the article. For example, the tutorial I ran at SC13 with Terry Hewitt titled "Effective Procurement of HPC Systems" was very popular (~100 attendees). We have provided similar training as part of...
(95 days ago)

Numerical Algorithms Group wrote a new blog post titled Testing Matrix Function Algorithms Using Identities

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 practice, rather than I, we might find that we obtain a matrix R close to I, perhaps with ||R-I||...
(164 days ago)

About:

The Numerical Algorithms Group (NAG) delivers trusted, high quality numerical computing software and high performance computing (HPC) services. For four decades NAG experts have worked closely with world-leading researchers in academia and industry to create powerful, accurate and flexible software which today is relied upon by tens of thousands of users, companies, and learning institutions as well as numerous independent software vendors.

From multicore workstations to the latest supercomputers, NAG's robust software development products, parallel software engineering services, independent technology consulting and HPC training can support your modelling and computing needs.

News

News: NAG announces support for IBM BlueGene/Q supercomputers

677 days ago - Numerical Algorithms Group

News: Fortran standards editor wins important IEC award

976 days ago - Numerical Algorithms Group

Products

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The NAG Fortran Library

Numerical Algorithms Group

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The NAG C Library

Numerical Algorithms Group