Parallel Computing
As one of the earliest adaptors of NVIDIA’s GPU technology for use in financial services, SciComp has many years of experience and a high level of expertise with GPU technology.
A key area of focus has been the GPU-enablement of derivatives pricing models and risk system components.
GPU Modeling Expertise
SciComp's NVIDIA trained quantitative development team, provides expert, cost-effective GPU programming services for any PDE (partial differential equation) or Monte Carlo based pricing model. In addition, SciComp consulting also GPU-enables pricing model calibration routines and risk system components.
SciFinance: GPU Pricing Code Without Programming
SciFinance® automatically creates derivative pricing models source code from high level specifications. SciGPU MC, the parallel computing component of SciFinance, automatically generates CUDA (NVIDIA GPU) source code for any Monte Carlo-based pricing model. Simply add the keyword “CUDA” to your model specification and SciFinance automatically generates the corresponding CUDA source code using its pre-implemented set of knowledge rules. Then test side-by-side the GPU-enabled code vs the default OpenMP-compliant code to verify the frequently order of magnitude accelerations while maintaining identical numerical results. The GPU-enabled code is structured to take advantage of current GPU hardware and software (CUDA) features. GPU or parallel programming expertise is not required.
