A fascinating slide deck of financial programming wizardry by Daniel Egloff of Quantlea at the NVIDIA Global Technology Conference, 2012, showing the real-world power of F# as a tool when applied in the GPGPU programming space:
Title: New Generation GPU Accelerated Financial Quant Libraries
New generation GPU accelerated solutions for derivative pricing, hedging, and risk management can be build more efficiently with modern technology and functional programming languages like F# on .NET or Scala on the Java VM. As a concrete example we report from a large derivative pricing project developed in F# on .NET. We will introduce the key design concepts and parallelization strategies, which lead to an efficient and transparent GPU acceleration. Several examples will illustrate the benefit of functional as compared to the classical object oriented approach.