Programming in OpenCL and its advantages in a GPU Framework
K S Harshavardhan · International Journal for Research in Applied Science and Engineering Technology · 2022
Abstract: OpenCL is a framework used for building applications that mostly run on heterogenous platforms containing CPUs, GPUs, and DSPs. OpenCL provides an interface for parallel programming that can be used to take advantage of the GPUs high parallel computing power. Programmers who need complete control over the parallelization process and who are required to write portable heterogeneous code mostly use OpenCL. OpenCL views a processing unit as a collection of compute units which in turn are made up work items. According to OpenCL’s workflow and memory hierarchy, each work item is a thread as far in terms of control and memory model. A collection of work items is called a work group which is mapped to a compute unit. The language used to write “compute kernels” is called kernel language. OpenCL uses C/C++ to carry over the kernel computations done on the device. The host code specifies the kernel specifications that is needed for the computation of the device which includes creating buffers, calling kernels, mapping the memory back to CPU from device, etc. OpenCL also has specific optimization techniques that helps improve parallelization while computing on a GPU which results in better performance numbers