I'm learning OpenCL and I have a compatible x86 CPU, but my GPU doesn't support OpenCL at all.
So when I call the clGetDevices API, it returns nothing.
As I'm just learning this framework and I'm not looking for optimization or higher performance, is it necessary to get a new system ? (While OpenCL programs are running on my platform)
Thanks in advance :)
http://www.acooke.org/cute/Developing0.html describes how i worked with a cpu (only) a few years ago. basically, the AMD OpenCL driver worked with my Intel CPU.
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I currently do not have an Nvidia GPU on my laptop but I still want to be able to speed up training. Per the Flux docs, it says Nvidia GPU's are supported out of the box but doesn't mention AMD GPU's at all. Is it possible to work with Flux on an AMD GPU?
This should in principle be possible, since AMDGPU.jl provides a similar interface for AMD GPUs as CUDA.jl does for NVIDIA GPUs, and Flux is claimed to be agnostic to array types. However, at best this will only work on Linux, since AMDGPU.jl relies on AMD's ROCm platform, and ROCm is only supported on Linux, since ROCm is indeed specifically built around the Linux kernel.
Do Nvidia GPUs support an OpenCL aware MPI, with similar functionality as its CUDA aware MPI?
Also, do AMD GPUs' OpenCL provide such functionality?
I would have thought a simple google search would have answered this, but surprisingly I did not find much info on this while there is a ton of info on CUDA aware MPI!
If I write a desktop application that requires OpenGL and OpenCL (and communication between the two--rendering based on opencl calculations), what are the situations where users will not be able to use it? Are we at the point where OpenCL is pretty much available on all desktops and laptops in the last 3 years?
All recent discrete GPUs support OpenCL, as do AMD APUs and CPUs. All Intel CPUs can be supported using the AMD APP SDK. Intel's OpenCL SDK has some limits on which CPUs and which Intel GPUs it supports. Therefore, your application will always be able to fall back to using the CPU if no supported GPUs are available. I have yet to meet a desktop without OpenGL. If everything is installed properly then you shouldn't have any problems.
Your biggest problems will come from driver bugs in both OpenCL and OpenGL implementations - my friends and I have seen a lot of this over the years.
I have seen that AMD APP SDK samples work on a machine having only Intel CPU.
How can this happen? How does the compiler target a different machine architecture?
Do I not need Intel's set of compilers for running the code on the intel CPU?
I think if we have to run an OpenCL application on a specific hardware, I have to (re)compile it using device's vendor specifics compiler.
Where is my understanding wrong?
Firstly, OpenCL is built to work on CPU's and GPU's. You can compile and run the same source code on either type of device. However, its very likely that CPU code will be sub-optimal for a GPU and vice-versa.
AMD H/W is 7% - 14% of total x86/x64 CPU's. So AMD must develop compilers for both AMD and Intel chips to be relevant. AMD have history developing compilers for both sets of chips. Conversely, Intel have developed compilers that either don't work on AMD chips or don't work that well. That's no surprise.
With OpenCL, the AMD APP SDK is the most flexible it will work well on AMD and Intel CPU's and AMD GPUs. Intel's OpenCL SDK doesn't even install on AMD x86 H/W.
If you compile an OpenCL program to binary, you can save and reuse it as long as it matches the OpenCL Platform and Device that created it. So, if you compile for one device and use on another you are very likely to get an error.
The power of OpenCL is abstracting the underlaying hardware and offer massive, parallel and heterogeneous computing power.
Some SDKs and platforms offers some specific features to "optimize" the code, i honestly think that such features are just marketing and they introduce boilerplate code making the application less portable.
There are also some pseudo-new technologies that are just wrappers to OpenCL or they are really similar in the concept like the Intel quick sync.
About Intel i should say that at the first place they were supporting all the iCore generation and even some C2D, now the new SDK only support the 3rd iCore generation, i don't get their strategy honestly, probably Intel is the last option if you want to adopt OpenCL and targeting the biggest possible audience, also their SDK doesn't seems to be really good at all .
Stick with the standard and you will avoid both possible legal and performance issues and your code will also be more portable.
The bottom line is that the AMD SDK includes a compiler for targeting x86 CPUs for OpenCL. That means that even though you are running an Intel CPU the generated code will run on it. It's the same concept as compiling a C program to run on an x86 CPU: it works on Intel and AMD CPUs (or any that implement the x86 instruction set).
The vendor's compiler might have specific optimizations, like user827992 mentions, but in my experience the performance of AMD's CPU compiler isn't that bad when running on an Intel CPU. I haven't tried Intel's OpenCL implementation.
It is true that for some (maybe most in the future) hardware, only the vendor's compiler will support it. AMD's SDK won't build code that will run on an NVIDIA card, and vice-versa. CPUs happen to be a bit of a special case in that the basic instruction set is so widely deployed that the CPU compiler will work on most machines you're likely to come in contact with.
With some friends we want to use openCL. For this we look to buy a new computer, but we asked us the best between AMD and Intel for use of openCL. The graphics card will be a Nvidia and we don't have choice on the graphic card, so we start to want buy an intel cpu, but after some research we figure out that may be AMD cpu are better with openCL. We didn't find benchmarks which compare the both.
So here is our questions:
Is AMD better than Intel with openCL?
Is it a matter to have a Nvidia card with an AMD cpu for the performance of openCL?
Thank you,
GrWEn
You shouldn't care as much about what CPU you use as much as what GPU you use. You would need to choose between an AMD/ATI GPU or nVidia GPU.
I would personally recommend an nVidia GPU as, in addition to OpenCL support, you can experiment with their more proprietary CUDA technology which offers a far richer development experience than OpenCL does today. While you're at it take a look at the new AMP technology that was just announced by Microsoft for C++ which aims to bring language extensions akin to nVidia's CUDA. nVidia also has offerings for the enterprise with their Tesla GPUs with several vendors offering GPU clusters and you can even get a GPU compute cluster on Amazon EC2 now which is all based on nVidia hardware.
You want to buy a new computer with your friends? What kind of project do you plan to do? The question about the hardware is answered with the needs you have. If you give some more information, we can provide better suggestions.
As written before, the CPU is not the important point as long as you do not want to buy a multiprocessor multicore system like 4 Quadprocessors. The difference in performance is mostly the differences of the GPUs used and there you can find different cards for all needs. From a cheap GPU to the nVidia Tesla cards.
It is definitely not a problem to run a nVidia board on a AMD system. I do it here. You also can use the OpenCL devices from the AMD Multicore CPU and the nVidia GPU in parallel.
You should pay attention: If you plan to buy a potent system to run your software (like a webserver), every developer of OpenCL software needs a system for testing. So every developer needs at least a modern multi-core CPU with an OpenCL SDK. Where the OpenCL kernels are developed does not matter. OpenCL is platform independed.
Both Intel and AMD have good OpenCL-support for their CPUs, so currently it does not really matter which you cooose. If you want to use the embedded GPU on AMD Fusion or Intel SandyBridge, then I suggest you go for Fusion since Intel does not have a driver for their GPUs (yet). Depending on what you are going to use OpenCL for, I could suggest a GPU - sometimes NVidia is faster, sometimes AMD.
AMP, CUDA, RenderScript and the many, many others all work nice but they don't work on all hardware as OpenCL does. CUDA certainly has advantages, but in the time you have learnt openCL I can assure you the tools around OpenCL have catched up.
The CPU has no influence on GPU OpenCL performance.
You might also want to try running the OpenCL kernels on CPU. Checkout the Intel OpenCL compiler beta. You can even run kernels on both CPU and GPU.