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Robotics and automation engineers benefit by using rigorously tested routines from Numerical Libraries

Manufacturing engineers, many of whom are already contending with slower performance of legacy applications originally developed for 32-bit processors that are now operating in 64-bit systems or supercomputer-level resources, can now obtain a white paper tailored for concerns of environmental researchers: The Benefits of Using Rigorously Tested Routines from Numerical Libraries — Manufacturing Engineering Edition by writing to

The Benefits of Using Rigorously Tested Routines from Numerical Libraries white paper is geared to help robotics and automation engineers understand how and why to incorporate use of extensively documented numerical libraries into their application development practices.

The subject matter discussed in the NAG Library Guide white paper is of growing importance to a wide range of finance, industrial, business, scientific research, and engineering applications because of recent multicore processor developments and the emergence of GPU chips and/or widespread access to high performance computing (HPC) resources.

Rob Meyer, NAG CEO and author of this white paper explains, “This white paper speaks to matters at the core of industry — from yield analysis and process control, quality assurance, and design of automated systems, etc — that rely on mathematical and statistical methods that ultimately affect time-to-market. To the extent that industrial engineers’ work involves significant numerical computation, it is timely to re-examine how computational frameworks are or are not designed for maximum performance.”

Meyer continues, “The Numerical Algorithms Group (NAG), a global not-for-profit numerical software development organisation that collaborates with world-leading researchers and practitioners in academia and industry, devotes considerable resources to ongoing development of what is arguably the world’s most extensive and rigorously tested numerical library — the NAG Library that is available to application developers in C+, C#, F#, FORTRAN, MATLAB, R, Maple and other environment including routines tuned for multi-core and parallel hardware configurations.

"In recent years, it became clear that many researchers in a wide range of disciplines have yet to grasp that we have entered a period where investments in software, not hardware, matter most. We penned this white paper to help educate a wide range of technical application developers on how they can use numerical libraries to develop software on par with the processing capabilities of multicore systems and HPC computing environments.”

To obtain a copy of this white paper write to

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