Traditionally OpenCL C was used to program the accelerators in OpenCL standard, later C++ for OpenCL kernel language was developed that inherited all functionality from OpenCL C but allowed to use C++ features in the kernel sources. OpenCL adopts C/ C++-based languages to specify the kernel computations performed on the device with some restrictions and additions to facilitate efficient mapping to the heterogeneous hardware resources of accelerators. The programming language that is used to write compute kernels is called kernel language. The host API provides handles on device memory buffers and functions to transfer data back and forth between host and devices. Consistency between the various levels in the hierarchy is relaxed, and only enforced by explicit synchronization constructs, notably barriers.ĭevices may or may not share memory with the host CPU. Not every device needs to implement each level of this hierarchy in hardware. per-element private memory ( registers _private).local memory: shared by a group of processing elements ( _local).read-only memory: smaller, low latency, writable by the host CPU but not the compute devices ( _constant).global memory: shared by all processing elements, but has high access latency ( _global).OpenCL defines a four-level memory hierarchy for the compute device: In addition to that C++ features can also be used when implementing compute kernel sources in C++ for OpenCL language. More recently Khronos Group has ratified SYCL, a higher-level programming model for OpenCL as a single-source DSEL based on pure C++17 to improve programming productivity.
Open cl studio portable#
In order to open the OpenCL programming model to other languages or to protect the kernel source from inspection, the Standard Portable Intermediate Representation (SPIR) can be used as a target-independent way to ship kernels between a front-end compiler and the OpenCL back-end.
: 15 An implementation of the OpenCL standard consists of a library that implements the API for C and C++, and an OpenCL C compiler for the compute device(s) targeted. The OpenCL standard defines host APIs for C and C++ third-party APIs exist for other programming languages and platforms such as Python, Java, Perl, D and. Programs in the OpenCL language are intended to be compiled at run-time, so that OpenCL-using applications are portable between implementations for various host devices. In addition to its C-like programming language, OpenCL defines an application programming interface (API) that allows programs running on the host to launch kernels on the compute devices and manage device memory, which is (at least conceptually) separate from host memory. How a compute device is subdivided into compute units and PEs is up to the vendor a compute unit can be thought of as a " core", but the notion of core is hard to define across all the types of devices supported by OpenCL (or even within the category of "CPUs"), : 49–50 and the number of compute units may not correspond to the number of cores claimed in vendors' marketing literature (which may actually be counting SIMD lanes). A single kernel execution can run on all or many of the PEs in parallel. : 17 A single compute device typically consists of several compute units, which in turn comprise multiple processing elements (PEs). Functions executed on an OpenCL device are called " kernels". It defines a C-like language for writing programs. OpenCL views a computing system as consisting of a number of compute devices, which might be central processing units (CPUs) or "accelerators" such as graphics processing units (GPUs), attached to a host processor (a CPU).
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