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The University of Southampton

Core Algorithms for High Performance Scientific Computing Event

24 September 2012
University of Warwick

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Event details

Event from Computational Modelling Group

Core Algorithms for High Performance Scientific Computing Mon, 24 Sep - Fri, 28 Sep '12, Centre for Scientific Computing, University of Warwick, UK.

CSC / NAG Autumn School.

Following successful schools in previous years, we are running this course again in September. Attendance is free to HECToR users and UK academics within the remit of one of the participating research councils (EPSRC, NERC and BBSRC). Other people, including those from commercial organisations, may attend on payment of a course fee. In previous years the school has been oversubscribed. Participants are encouraged to register early to avoid disappointment. Registration is via the HECToR website:

Many scientific calculations can be cast as problems in computational linear algebra and optimisation. Powerful algorithms for such problems form a common core of most scientific software. This school will develop a solid grounding in the mathematics of these algorithms; discuss the efficient implementation in a range of standard libraries and demonstrate effective use in real, high-performance scientific applications. Aimed at: This school is ideal for beginning PhD students or Postdocs in all scientific disciplines wishing to make effective use of substantial computational resources to tackle new scientific problems. Prerequisites: Please note that this course does not teach a computer programming language.

A good working knowledge of a scientific programming language (either Fortran- 95/2003 or C/C++) is a pre-requisite. Students will also be assumed to be familiar with basic Linux commands, text editors, and compilation of scientific code in a command-line environment.

An event from our Computational Modelling Group

Bringing together Southampton university researchers using applied Computational Modelling to support the understanding and advancement of physical and natural sciences, engineering, medicine, economy, society, psychology.

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