Sponsored in part by NVIDIA, at the University of Utah they are exploring speeding up the Linux kernel by using GPU acceleration. Rather than just allowing user-space applications to utilize the immense power offered by modern graphics processors, they are looking to speed up parts of the Linux kernel by running it directly on the GPU.
From the project page: “The idea behind KGPU is to treat the GPU as a computing co-processor for the operating system, enabling data-parallel computation inside the Linux kernel. This allows us to use SIMD (or SIMT in CUDA) style code to accelerate Linux kernel functionality, and to bring new functionality formerly considered too compute intensive into the kernel. Simply put, KGPU enables vector computing for the kernel.”
Additionally, “it makes the Linux kernel really parallelized: it is not only processing multiple requests concurrently, but can also partition a single large requested computation into tiles and spread them across the large number of cores on a GPU.”