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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 ...
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 .
Intel Advisor: Linux and Windows. Viewer only on macOS. C, C++, Data Parallel C++ and Fortran A collection of design and analysis tools - vectorization (SIMD) optimization, thread prototyping, automated roofline analysis, offload modeling and flow graph analysis Freeware and Proprietary. Available as part of Intel oneAPI Base Toolkit.
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]
Intel Advisor (also known as "Advisor XE", "Vectorization Advisor" or "Threading Advisor") is a design assistance and analysis tool for SIMD vectorization, threading, memory use, and GPU offload optimization. The tool supports C, C++, Data Parallel C++ (DPC++), Fortran and Python languages.
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 ...
In computing, CUDA is a proprietary [2] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
Intel DAAL supported three processing modes: Batch processing: When all data fits in the memory, a function is called to process the data all at once. Online processing (also called Streaming): when all data does not fit in memory. Intel® DAAL can process data chunks individually and combine all partial results at the finalizing stage.