NAG provides expertise in numerical engineering, by delivering high-quality computational software, consulting services and high performance computing services. For over four decades NAG have collaborated with world-leading experts to create powerful, reliable and flexible software which is relied on by tens of thousands of individual users, as well as numerous independent software vendors. As a not-for-profit company, NAG reinvests surpluses into the research and development of its products, services, staff and its collaborations.
NAG was founded in 1970 as an inter-University collaborative venture combining the talents of many globally renowned mathematicians. In 1971 NAG developed the first mathematical software library - the NAG Library, which, over the next four decades, has evolved to become the largest commercially available collection of high quality mathematical and statistical algorithms. NAG's commitment to testing and quality remains steadfast. Alongside the Library, NAG develops the NAG Compiler. NAG's products are expertly and directly supported by NAG's technical team.
Universities with other types of computers became interested in the activity, and various machine-range implementations were initiated from Mark 2 of the Library onwards. Hence, the early aims of NAG could be summarised as follows:
- To create a balanced, general-purpose library of algorithms which meets the numerical and statistical needs of computer users.
- To support the Library with documentation giving advice on problem identification, algorithm selection, and routine usage.
- To provide a substantial test suite, including example test programs, for certification of the Library.
- To implement the Library as widely as user demand required.
NAG has a breadth of HPC experience and expertise that combines skills found in large HPC centres with specialist business focused HPC skills.
With decades of experience in maths, statistics, coding and computer science, NAG experts help organizations find and implement optimum numerical solutions.
NAG software products help solve complex mathematical problems in specialist areas like optimization, algorithmic differentiation and many more.
Organizations from a diverse set of industries and academic areas rely on NAG to power their numerical capabilities. See how they benefit from NAG's software and services.
We round up our most interesting and informative technical and collaborative news stories and publish them direct to our subscribers every 6 weeks.
Learn of opportunities to work at the Numerical Algorithms Group and see the many benefits that NAG staff enjoy!
The breadth and depth of expertise within NAG's technical team of mathematicians and computer scientists is used to provide HPC support to supercomputing centres around the world. NAG HPC Services provides procurement advice, consulting services and people with expert computational science engineering skills either onsite at client premises or supports users from NAG offices.
NAG's ethos is, collaborative, consultative, consensus-based, principled and transparent. It was founded on collaboration and continues to do so with expert individuals and organizations from industry and academia all over the world.
NAG Numerical Services help organizations find and implement the optimum numerical computation solutions from teaching the best ways to solve complex problems or verifying that older applications remain valid and optimal for the latest processors and platforms. NAG can be used to provide bespoke training courses and works with teams at organizations to impart skills and techniques that will help solve your numerical problems.
Application and software organizations embed NAG software and services when demand dictates the need for analytical techniques such as modelling, forecasting, optimization and data mining via the NAG Partnership Program.
Similarly, the world's leading computer hardware manufacturers work closely with NAG to ensure that NAG software is optimized for their customers. Additionally, NAG Numerical Services have been enlisted to help develop some externally produced core numerical libraries.