#1 Mon Apr 23, 2012 3:22 pm
Registered: Jun 2010
ACCELERATING SCIENTIFIC COMPUTATION: THE DATAFLOW APPROACH
2-6 July 2012
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 new dataflow approach for accelerating computation, which has recently 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, biophysics, and quantum chemistry. Promising results are reported. The topics addressed include:
- Monte Carlo simulation
- numerical solutions of ordinary and partial differential equations
- numerical integration methods
- finite difference and finite elements methods
- ab initio quantum chemistry
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.
The Registration Fees for this Summer School is as follows:
- On or before 1 June 2012 - Regular Fee: GBP 399, Student Fee: GBP 350
- From 2 June 2012 - Regular Fee: GBP 499, Student Fee: GBP 399
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. Rooms at local hotels and student accommodation should be available.
Further information of the Summer School, including a preliminary schedule, can be found at:http://cc.doc.ic.ac.uk/asc12