About the Project
Recent developments by Xilinx result in a very exciting time at the moment, as these advances make it a far more realistic proposition than ever before to accelerate codes using FPGAs. Firstly, we have seen great improvements in hardware capability, where in the past couple of years the chips themselves have become much more powerful than ever before. Secondly, Xilinx released their Vitis software development platform around 6 months ago, and this is a game changer when it comes to programmability. Whilst programming was always traditionally one of the big challenges, it now is possible to use C or C++, and writing code for FPGAs is now much more a question of software development rather than hardware design.
This project will work with Xilinx to explore the use of FPGAs for accelerating quantitative finance software codes. Depending upon the exact interests of the student, the quantitative finance applications can either be the primary focus, or alternatively used more as a vehicle to help evaluate a wider range of research conducted around FPGAs. The bullets below illustrate starting points for these two areas of focus:
• Xilinx have already developed a number of open source building blocks for quantitative finance codes, with some very promising results. But realistically they have only just scratched the surface of what’s possible here, to support the finance community in general. In collaboration with Xilinx, we will select a number of high priority finance algorithms for FPGA acceleration, and then explore the porting and acceleration of these on FPGAs using the most appropriate algorithmic techniques which we will likely need to develop.
• Alternatively we could focus more on the wider software eco-system for FPGAs. For instance, whilst the Vitis platform has provided significant advances in programming, there is still much work to be done around the tooling, including the most appropriate way of profiling these sorts of codes and supporting the development of appropriate dataflow style algorithms. This area of focus would use the area of quantitative finance as a vehicle to evaluate the research conducted.
This PhD work is of great interest to Xilinx and will potentially benefit many in their customer base and the wider FPGA community. As such there would co-supervision from at-least one Xilinx member of staff, frequent visits to Xilinx offices, and access to the latest generation FPGA technologies. The student themselves would be based at EPCC and and also have access to other EPCC-run systems and EPCC’s rich training opportunities.
This PhD opportunity is based within EPCC (https://www.epcc.ed.ac.uk), a Centre of Excellence within the College of Science and Engineering at the Unviersity of Edinburgh, and one of Europe’s leading supercomputing centres.
A UK 2:1 honours degree, or its international equivalent, in a relevant subject such as computer science and informatics, physics, mathematics, engineering, biology, chemistry and geosciences. You must be a strong programmer, ideally with experience in one of C or C++ although these specific languages are not a prerequisite.
Recommended/Desirable Skills and Experience:
• Understanding of HPC programming concepts
• Strong programmer, ideally with experience in one of C or C++
• Masters degree in a related field
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.