The F# GPU Symbiosis – How to Develop Ultra-Fast Code More Quickly

Session Title

The F# GPU Symbiosis – How to Develop Ultra-Fast Code More Quickly

Speaker

Dr. Daniel Egloff

Audience Level

All

Abstract

F# and GPUs are an ideal combination to solve numerically intensive problems in scientific computing, machine learning and large scale data analysis. The new Alea GPU compiler platform radically simplifies the development of GPU accelerated .NET applications. With Alea GPU you gain cross platform compatibility, improve productivity and increase development agility.

With some concrete use cases we show how F# and GPUs can enhance computation speed, user experience and generate additional business value. For the technically oriented audience we run a short live coding session to illustrate the capabilities of Alea GPU.

Audience Takeaway

• Getting introduced to GPUs, CUDA and GPU computing on .NET

• Use cases in quant finance and machine learning for algorithmic trading

• Understanding how to use Alea GPU prefabricated algorithms for real world applications by solving some problems originating from random forest training with GPUs

Speaker Bio

Dr. Daniel Egloff

Partner InCube Group, Managing Director QuantAlea

In 2008 Daniel Egloff set up his own software engineering and consulting company and founded QuantAlea by the end of 2009. Since then he has advised several high profile clients on quantitative finance, software development and high performance computing. In 2014 QuantAlea and InCube merged and he became partner of InCube Group and Managing Director of QuantAlea. He is a well-known expert in GPU computing and parallel algorithms and successfully applied GPUs in productive systems for derivative pricing, risk calculations and statistical analysis. Before setting up his own company he had spent more than fifteen years in the financial service industry, where his work revolved around derivative pricing, risk management with a special focus on market and credit risk, and high performance computing on clusters and grids. He studied mathematics, theoretical physics and computer science at the University of Zurich and the ETH Zurich, and has a PhD in mathematics from the University of Fribourg, Switzerland.