Alea.cuBase – A Language Integrated Compiler for CUDA in F#
We introduce the brand new version of Alea.cuBase. It is a full F# to GPU compiler and linker, integrated into F#, extending F# to a first class CUDA language, with support for many of the new CUDA 5.5 features.
We explore how F# can be used to script GPU algorithms, dynamically generate CUDA kernels, compile and execute them on the fly and interactively improve the algorithms. A few live coding examples will give you a flavor of the agility and power of the new development tools and show how to solve performance demanding numerical problems.
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 2012 he joined InCube Advisory to further strengthen their consulting capabilities, continuing to manage QuantAlea as a software engineering provider. Over the last few years he has become 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.