- #Cuda vs opencl benchmark pro#
- #Cuda vs opencl benchmark software#
- #Cuda vs opencl benchmark professional#
What Are the Strengths of the OpenCL Platform? Regardless of this, CUDA is still supported by a wide variety of apps of which the list continues to grow.Īs an easy rule of thumb, if your app supports CUDA, grab an Nvidia card, even if it also supports OpenCL. However, CUDA is not as easy for apps to adopt as OpenCL (as it is open-source). Obviously, because CUDA is a proprietary framework it requires Nvidia’s support and time to integrate it into applications, this means that the functionality is always fantastic. If you enable OpenCL, only 1 GPU can be utilised, however, when CUDA is enabled 2 GPUs can be used for GPGPU. For further reading, in a forum thread on Creative Cow, an Adobe employee stated that in most cases CUDA would out-perform OpenCL ( source).Īnother good example of the difference between CUDA and OpenCL support can be seen in REDCINE-X.
#Cuda vs opencl benchmark pro#
If we look at Premiere Pro CS6, without CUDA only software-based playback is available ( source). For example, if we look at the Adobe CC, which supports both CUDA and OpenCL, CUDA accelerates more features and provides better acceleration to the features that both frameworks are able to power. The main reason for this is that Nvidia provide top quality support to app developers who choose to use CUDA acceleration, therefore the integration is always fantastic. The general consensus is that if your app of choice supports both CUDA and OpenCL, go with CUDA as it will generate better performance results. Each of these approaches brings their own pros and cons which we will highlight in this section. What Are the Strengths of CUDA Acceleration?Īs we have already stated, the main difference between CUDA and OpenCL is that CUDA is a proprietary framework created by Nvidia and OpenCL is open source. We can only see Nvidia’s OpenCL performance getting better and better in the future, and this is definitely something worth considering. This is changing though as the recently released Nvidia GTX 980 is a very capable OpenCL card as well as a CUDA monster. It should be noted that Nvidia cards actually support OpenCL as well as CUDA, they just aren’t quite as efficient as AMD GPUs when it comes to OpenCL computation. Don’t worry, that’s what we’re going to help you with today. Or “so if my application supports both, which should I go for?”. Naturally, your next question will be “does my application of choice support CUDA or OpenCL?”. Different apps support different GPGPU frameworks, in fact, some support both OpenCL and CUDA and some support neither. So which framework do the major applications support you may ask? This is where things can get a little more complicated. To cut to the chase, AMD support OpenCL and Nvidia support their own proprietary CUDA framework.
Where Do Nvidia & AMD Sit in the GPGPU Spectrum?įortunately, AMD & Nvidia have made the debate slightly more black and white than it may have originally seemed. CUDA, on the other hand, is the leading proprietary GPGPU framework. So now you know what GPGPU is, how do OpenCL and CUDA fit into the equation? OpenCL is currently the leading open source GPGPU framework. If the application you use supports OpenCL or CUDA, you will normally see huge performance boosts when using hardware that supports the relevant GPGPU framework. Such bidirectional processing can hugely improve efficiency in a wide variety of tasks related to images and video. GPGPU allows information to be transferred in both directions, from CPU to GPU and GPU to CPU. In traditional computing, data can be passed from the CPU to the GPU, the GPU then renders the data, but the GPU cannot pass information back. GPGPU is the utilisation of a GPU (graphics processing unit), which would typically only handle computer graphics, to assist in performing tasks that are traditionally handled solely by the CPU (central processing unit). So what exactly is GPGPU, or general purpose computing on graphics processing units?
#Cuda vs opencl benchmark software#
OpenCL and CUDA are software frameworks that allow GPGPU to accelerate processing in applications where they are respectively supported.
#Cuda vs opencl benchmark professional#
If you’ve never heard of GPGPU or GPU acceleration, don’t worry, most people haven’t, but custom Apple computer experts like ourselves do, and we can explain! OpenCL and CUDA, however, are terms that are starting to become more and more prevalent in the professional computing sector. Introduction to GPGPU (General Purpose Computing on Graphics Processing Units) Finally, we will explain which applications work best with which brand of graphics cards, providing a list that gives a brief overview of CUDA/OpenCL support in a wide variety of professional apps. We’ll give you a brief overview of what GPGPU is and look at how AMD, Nvidia, OpenCL & CUDA fit into the mix. It’s a GPGPU/GPU Acceleration real-world face-off we’ve got on our hands here! If you’re looking for more information on CUDA and OpenCL, this is the article for you.
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