JASMIN with NAG* presented a free workshop on the Python bindings of the famous NAG Numerical Library on 28th November 2018. If you would like to request a repeat of this event, please contact the helpdesk.
The presenters will give an overview of NAG and how the Python interface works on JASMIN with an interactive session for solving your particular technical computing problem using the NAG Numerical Library.
This workshop is aimed at anyone using the Python language for numerical computing and wanting to increase productivity, improve reliability and accuracy of their numerical analysis. This workshop will also be beneficial for developers of other languages such as C, C++ and Fortran, and technical experts from NAG will be available to discuss your numerical computing needs for your research.
This half day workshop will take place at RAL and a draft timetable can be seen below (subject to minor change). Further details will be sent to attendees in due course. More details about the NAG Python interface can also be found here. Ticket sales will end on 26th November at 6pm, or when capacity has been reached. Further details about the day will be sent in advance of the event to registered attendees.
NAG have just announced the availability of the new NAG Library for Python. The re-engineering of the NAG Library for Python offers many usability improvements enabling quicker application development including, self-contained routine documentation, thread-safety, curated examples demonstrating important algorithmic and Python-related functionality, support for native Python callbacks and C language routine equivalents giving a unified route from prototyping in Python to deploying as compiled code.
NAG Library for Python key features and benefits of this release:
· Fully Pythonic interfaces optimized for usability
· Full integration with native Python IO
· Flexible data types, particularly for string and integer input, and NumPy-compatible array-like arguments accepted
· Support for native Python callbacks
· namedtuple function return data
· Curated examples within the package give short demonstrations of important algorithmic and Python-related functionality
· Ability to utilize Intel MKL through the Library
· Self-contained API documentation
· Row-ordered or column-ordered input permitted
All routines have C and Fortran equivalents, giving a unified route from prototyping your code in Python to deploying as compiled code.
13:00 Opening by CEDA/JASMIN
13:10 How to request access to NAG libray on JASMIN
13:30 NAG introduction
13:45 The NAG library
Including the new reengineered release of the NAG Library for Python
14:30 Coffee break
15:00 Demonstration on using NAG/Python on JASMIN
16:00 Bring your own numerical problem
16:30 Feedback & closing
* The Numerical Algorithms Group (NAG) are pleased to visit to provide an introduction to NAG, along with products and services, many of which are available under the existing license agreement with NERC. NAG delivers high quality numerical software and high performance computing (HPC) services.
NAG’s Numerical Library underpins thousands of applications used around the world in fields such as finance, science, engineering, academia, and research. Since its first release more than forty years ago, it has been widely trusted because of its unrivalled accuracy, reliability and portability, having been implemented on multiple platforms ranging from PC workstations to the world's largest supercomputers.