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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.

Features CUDA 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

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