Obtaining high compute performance on today’s modern computer
architectures requires code that is optimized, power-efficient, and
scalable. The demand for high performance continues to increase due to
needs in AI, video analytics, data analytics, as well as in traditional
high-performance computing (HPC).
Modern workload diversity has resulted in a need for architectural
diversity; no single architecture is best for every workload. A mix of
scalar, vector, matrix, and spatial (SVMS) architectures deployed in
CPU, GPU, AI, and FPGA
is required to extract the needed performance.
Today, coding for CPUs and accelerators requires different languages,
libraries, and tools. That means each hardware platform requires
separate software investments and provides limited application code
reusability across different target architectures.
The oneAPI programming model simplifies the programming of CPUs and
accelerators using modern C++ features to express parallelism using SYCL*.
SYCL enables code reuse for the host (such as a CPU) and
accelerators (such as a GPU) using a single source language, with
execution and memory dependencies clearly communicated. Mapping within
the SYCL code can be used to transition the application to run on the
hardware, or set of hardware, that best accelerates the workload. A host
is available to simplify development and debugging of device code, even
on platforms that do not have an accelerator available.
oneAPI also supports programming on CPUs and accelerators using the
OpenMP* offload feature with existing C/C++ or Fortran code.
Not all programs can benefit from the single programming model
offered by oneAPI. It is important to understand how to design,
implement, and use the oneAPI programming model for your program.
Learn more about the oneAPI initiative and programming model at
. The site includes the oneAPI
Specification, SYCL Language Guide and API Reference, and other