A Comparison of SYCL, OpenCL, CUDA, and OpenMP for Massively Parallel Support Vector Machine Classification on Multi-Vendor Hardware
Marcel Breyer, Alexander Van Craen, Dirk Pflüger
Abstract
In scientific computing and Artificial Intelligence (AI), which both rely on massively parallel tasks, frameworks like the Compute Unified Device Architecture (CUDA) and the Open Computing Language (OpenCL) are widely used to harvest the computational power of accelerator cards, in particular of Graphics Processing Units (GPUs). A few years ago, GPUs from NVIDIA were used almost exclusively for these tasks but meanwhile, AMD and Intel are increasing their shares of the GPUs market. This introduces many new challenges for code development, as the prevailing CUDA code can only run on NVIDIA hardware and must be adapted or even completely rewritten to run on GPUs from AMD or Intel.
Topics & Concepts
CUDAComputer scienceParallel computingMassively parallelGeneral-purpose computing on graphics processing unitsCode (set theory)GraphicsVendorGraphics processing unitComputer architectureOperating systemProgramming languageSet (abstract data type)BusinessMarketingParallel Computing and Optimization TechniquesNeural Networks and ApplicationsAdvanced Neural Network Applications