Using GPGPU in Calculation Performance

FlexSystem General Purpose GPU processing (GPGPU) has been designed to utilize both the CPU and GPU for processing where the main processing CPU offloads to the GPU both CPU intensive and time intensive processes thus freeing up the CPU to crunch numbers and assign tasks to other parts of the computer and in so doing allows the applications to run significantly faster. Significant changes were made by Nividia to allow these GPUs to be accessed and addressed by programmers and the resultant language to enable this process was called CUDA.

A typical computer has the CPU within one single physical component and typically contains 4 to 8 cores, each core being a CPU under the command of the main processor that can run on a concurrent basis. The GPU contains hundreds of cores (for example Nvidia GeForce GTX 680 has 1,536 cores and utilizes Kepler Architecture) and is massively parallel allowing the CPU and GPU to crunch through massive volumes of computations at high speed.

By leveraging GPGPU technology in FlexSystem’s spreadsheet reporting tool, i.e. FIONQX, some complex financial reports that used to take up 30 minutes can now be completed in 6 seconds.