CUDA vs OpenCL | Difference between CUDA and OpenCL
This page compares CUDA vs OpenCL and mentions difference between CUDA and OpenCL.
CUDA
• 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.
OpenCL
• 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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