CUDA vs OpenCL | Difference between CUDA and OpenCL
This page compares CUDA vs OpenCL and mentions difference between CUDA and OpenCL.
• It is parallel computing platform and
programming model developed by NVIDIA corporation.
• It allows engineers to use CUDA enabled GPU for general purpose processing. This is known as GPGPU.
• CUDA platform is layer which provides direct access to instruction set and computing elements of GPU to execute kernel.
• CUDA platform works with C, C++, fortran.
• Supports operating systems e.g. windows XP and later, macOS, Linux.
• It is developed by Khronos Group and written in C/C++.
• It is a framework to write programs which execute across heterogeneous platforms. It consists of CPUs, GPUs, DSPs, FPGAs, hardware accelerators and other processor types.
• It provides standard interface for parallel computing with the help of task based and data based parallelism.
• Supports operating systems e.g. Android, FreeBSD, Windows, Linux, macOS etc.
Following table mentions comparison between CUDA and OpenCL.
|Compilation options||Offline oly||Online and Offline|
|math precision||Undefined||very well defined|
|math library||Proprietary||standard defined|
|native support||No native thread support available||task parallel compute model with ability to enqueue native threads|
|extension mechanism||proprietary||defined mechanism|
|Vendor support||NVIDIA only||industry wide support AMD, Apple etc.|
|C language support||Yes||Yes|
|Function||use compiler to build kernels||build kernels at runtime|
|Buffer offset||Allowed||Not allowed|
|Abstraction of memory/core hierarchy||blocks/threads, shared memory||work group/item|
|explicit data mapping and movement||CudaMemcpy function||bufferWrite function|
|Event driven, pipeline||stream||pipe|