Search results
Results From The WOW.Com Content Network
oneAPI is an open standard, adopted by Intel, [1] for a unified application programming interface (API) intended to be used across different computing accelerator (coprocessor) architectures, including GPUs, AI accelerators and field-programmable gate arrays. It is intended to eliminate the need for developers to maintain separate code bases ...
The third leg of the stool in Intel's turnaround is its OneAPI software platform. Nvidia has a 15-year head start in developing its CUDA software to program GPUs, with a substantial installed base ...
CUDA competes with other GPU computing stacks: Intel OneAPI and AMD ROCm. Whereas Nvidia's CUDA is closed-source, Intel's OneAPI and AMD's ROCm are open source.
Nvidia's CUDA is closed-source, whereas AMD ROCm is open source. There is open-source software built on top of the closed-source CUDA, for instance RAPIDS . CUDA is able run on consumer GPUs, whereas ROCm support is mostly offered for professional hardware such as AMD Instinct and AMD Radeon Pro .
The library supports Intel and compatible processors and is available for Linux, macOS and Windows. It is available separately or as a part of Intel oneAPI Base Toolkit. [4] Intel IPP releases use a semantic versioning schema, so that even though the major version looks like a year (YYYY), it is not technically meant to be a year. So it might ...
ROCm HIP targets Nvidia GPU, AMD GPU, and x86 CPU. HIP is a lower-level API that closely resembles CUDA's APIs. [47] For example, AMD released a tool called HIPIFY that can automatically translate CUDA code to HIP. [48] Therefore, many of the points mentioned in the comparison between CUDA and SYCL also apply to the comparison between HIP and ...
Intel oneAPI DPC++/C++ Compiler is available for Windows and Linux and supports compiling C, C++, SYCL, and Data Parallel C++ (DPC++) source, targeting Intel IA-32, Intel 64 (aka x86-64), Core, Xeon, and Xeon Scalable processors, as well as GPUs including Intel Processor Graphics Gen9 and above, Intel X e architecture, and Intel Programmable Acceleration Card with Intel Arria 10 GX FPGA. [5]
OpenCL is actively supported on Intel, AMD, Nvidia, and ARM platforms. The Khronos Group has also standardised and implemented SYCL, a higher-level programming model for OpenCL as a single-source domain specific embedded language based on pure C++11. The dominant proprietary framework is Nvidia CUDA. [13]