Summary
This white paper discusses the application of graphical processing units (GPUs) in actuarial modeling, focusing on their computational advantages and potential use cases. It begins by outlining the evolution of GPUs, highlighting their transition from graphics processing to general-purpose computing, particularly through frameworks like CUDA and OpenCL. The paper explains the architectural differences between CPUs and GPUs, emphasizing the parallel processing capabilities of GPUs that allow for faster calculations. It details the types of calculations that GPUs excel at, such as single instruction, multiple data (SIMD) operations, and the significance of CUDA cores and their variations for different numerical data types. The document also compares the performance of contemporary consumer GPUs with older server-grade GPUs, particularly in terms of floating-point operations per second (FLOPS) and precision levels required for actuarial computations. Additionally, it addresses the implications of memory availability and the impact of specialized cores on performance in actuarial applications.
