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Summer School on Accelerating Scientific Computation

Accelerating Scientific Computation: the Dataflow Approach
8-12 July 2013

Huxley Building, Imperial College London

There are great challenges in the development of scientific computation: data sets are growing exponentially, models are becoming increasingly complex, while many of the latest machines are getting more costly and harder to program.

This Summer School will provide an introduction to a dataflow approach for accelerating computation, which has been proven commercially. This approach involves compiling dataflow programs into special-purpose compute engines targeting advanced reconfigurable hardware. It has been used in many scientific computations, including those in geophysics, quantum chemistry, and bioinformatics. Promising results are reported. The topics addressed include:

  • nanophotonics
  • quantum chemistry
  • Monte Carlo simulation
  • n-body problems
  • numerical solution of differential equations
  • numerical integration techniques
  • finite difference methods
  • stencil computation

The Summer School will consist of talks given by leading experts from academia and from industry. There will be practicals to enable attendants to have hands-on experience of developing solutions using this approach. Attendants are invited to bring some of their problems, which can be used as case studies to illustrate the development and optimisation of designs. A preliminary schedule of the Summer School is available.

The Registration Fees for this Summer School are as follows:

If the fee is paid by credit card, a 1.345% processing fee will be added. The Registration Fee includes course material, refreshments during morning and afternoon breaks, five lunches, and two dinners. Accommodation is not included in the Registration Fee. Please check availability of local hotels and student accommodation; early booking is recommended. You could also try a booking service.

If interested, please register as soon as possible. For further information, please contact w.luk@imperial.ac.uk.