Mine is a "NVIDIA GeForce 9500 GS" and everywhere I've searched I can only find "9500 GT" ... does that mean the 9500 GS does not support any GPGPU language such as CUDA?
That's the official list :
http://www.nvidia.com/object/cuda_learn_products.html
Your 9500GS isn't listed so I'd say no ... but that's trivial to test, just download the sdk and run the example app ...
Is that a 9500M GS? If so, it has CUDA support
http://www.nvidia.com/object/product_geforce_9500m_gs_us.html
All post-G80 GPUs should have CUDA support
Related
I want to use TensorFlow on Windows (Win 10) with a AMD GPU.
If I google, there are a lot discussions and sources but I just couldn't figure out what's the best way to do this at the moment.
Could someone write a short installation instruction that he thinks is the best and most up-to-date way of doing so?
Tensorflow officially only supports CUDA, which is a proprietary NVIDIA technology. There is one unofficial implementation using openCL here which could work, or you could try using Google colab
I am wondering that whether nvidia supports spir backend or not? if yes, i couldn't find any document and sample example about that. but if not, is there a any way to work spir backend onto nvidia gpus?
thanks in advance
Since SPIR builds on top of OpenCL version 1.2, and so far Nvidia has not made any OpenCL 1.2 drivers available, it is not possible to use SPIR with Nvidia GPUs. As mentioned in the comments, Nvidia has made PTX available as intermediate language (also based on LLVM IR). One could consider translating SPIR into PTX but I don't know how realistic that would be.
Other vendors such as AMD and Intel are already showing support for SPIR. This can be verified by querying the CL_DEVICE_EXTENSIONS with the clGetDeviceInfo OpenCL API. If the result string contains cl_khr_spir, the driver supports SPIR.
I'm currently developing an OpenCL-application for a very heterogeneous set of computers (using JavaCL to be specific). In order to maximize performance I want to use a GPU if it's available otherwise I want to fall back to the CPU and use SIMD-instructions. My plan is to implement the OpenCL-code using vector-types because my understanding is that this allows CPUs to vectorize the instructions and use SIMD-instructions.
My question however is regarding which OpenCL-implementation to use. E.g. if the computer has a Nvidia GPU I assume it's best to use Nvidia's library but if no GPU is available I want to use Intel's library to use the SIMD-instructions.
How do I achieve this? Is this handled automatically or do I have to include all libraries and implement some logic to pick the right one? It feels like this is a problem that more people than I are facing.
Update
After testing the different OpenCL-drivers this is my experience so far:
Intel: crashed the JVM when JavaCL tried to call it. After a restart it didn't crash the JVM but it also didn't return any usable
devices (I was using an Intel I7-CPU). When I compiled the
OpenCL-code offline it seemed to be able to do some
auto-vectorization so Intel's compiler seems quite nice.
Nvidia: Refused to install their WHQL-drivers because it claimed I didn't have Nvidia-card (that computer has a Geforce GT 330M). When
I tried it on a different computer I managed to get all the way to
create a kernel but at the first execution it crashed the drivers
(the screen flickered for a while and Windows 7 said it had to
restart the drivers). The second execution caused a bluee-screen of
death.
AMD/ATI: Refused to install 32-bit SDK (I tried that since I will be using a 32-bit JVM) but 64-bit SDK worked well. This is the only
driver which I've managed to execute the code on (after a restart
because at first it gave a cryptic error-message when compiling).
However it doesn't seem to be able to do any implicit vectorization
and since I don't have any ATI GPU I didn't get any performance
increase compared to the Java-implementation. If I use vector-types I
might see some improvements though.
TL;DR None of the drivers seem ready for commercial use. I'm probably better of creating JNI-module with C-code compiled to use SSE-instructions.
First try to understand hosts & devices: http://www.streamcomputing.eu/blog/2011-07-14/basic-concept-hosts-and-devices/
Basically you can just do exactly what you described: check if a certain driver is available and if not, try the next one. What you choose first depends completely on your own preference. I would pick the device I have tested my kernel best on. In JavaCL you can pick the fastest device with JavaCL.createBestContext and CLPlatform.getBestDevice, check the host-code here: http://ochafik.com/blog/?p=501
Know NVidia does not support CPUs via their driver; only AMD and Intel do. Also is targeting multiple devices (say 2 GPUs and a CPU) a bit more difficult.
There is no API providing what you want. however, you can do the following:
i suggest you iterate over clGetPlatformIDs and query for the number of devices (clGetDeviceIDs), and device type for each device;
and pick the platform which has both types.
then build a map in u'r code, that maps for each type the list of platforms supporting it, ordered in some manner.
finally, just get the first item in the list corresponding for CL_DEVICE_TYPE_CPU and the first item corresponding for CL_DEVICE_TYPE_GPU.
if both returned results are equal (platform_cpu == platform_gpu) then pick one of them and use it for both.
if there is a platform supporting both, you will get match as before since you got order lists. then u can also do load balancing if u like on a single platform, like what Intel has.
Sorry for being late to the party, but regarding Intel's implementation behaviour under JavaCL, I'm afraid you've been bitten by a JavaCL bug :
https://github.com/ochafik/nativelibs4java/issues/297
Fixed in JavaCL 1.0.0-RC2 !
Cheers
How can I know which CPU can be programmed by OpenCL?
For example, the Pentium E5200.
Is there a way to know w/o running and querying it?
OpenCL compatibility can generally be determined by looking on the vendor's sites. AMD's APP SDK requires CPUs to support at least SSE2. They also have a list of currently supported ATI/AMD video cards.
The most official source is probably the Khronos conformance list:
http://www.khronos.org/conformance/adopters/conformant-products#opencl
For compatibility with the AMD APP SDK: http://developer.amd.com/gpu/AMDAPPSDK/pages/DriverCompatibility.aspx
For the NVIDIA, anything that supports CUDA should support their implementation of OpenCL:
http://www.nvidia.com/object/cuda_gpus.html
For compatibility with the Intel OpenCL SDK, look at:
https://software.intel.com/en-us/articles/opencl-code-builder-release-notes
Here is the list of conforming OpenCL products from the Khronos site:
http://www.khronos.org/conformance/adopters/conformant-products/
You got Intel OpenCL too http://software.intel.com/en-us/articles/intel-opencl-sdk/ for windows right now.
Just one more comment about Intel, Now they do not only support OpenCL under windows, but also linux. But it is part of a commercial SDK see https://software.intel.com/en-us/intel-media-server-studio.
Another alternative for OpenCL development under Linux is Beignet, an OpenCL source project maintain by Intel China.
http://www.freedesktop.org/wiki/Software/Beignet/
I have tested on linux and it works as per tutorial, however, the compiler they use is completely different from the one under the windows.
Well for the CPU, AMD's SDK is supposed to work on x86 (even on Intel's x86), so that will cover most of your options.
And for the GPU, I think almost all cards made in the last couple of years should run OpenCL kernels. I don't have of a particular list.
EDIT: Looks like AMD removed the original SDK pages with no replacement. There are unofficial mirrors for Windows and Linux, but I haven't tried them.
I am interested in a way how to read GPU temperature (graphics processing unit, main chip of graphic card), by using some video card driver API?
Everyone knows that there two different chip manufacturers (popular ones, at least) - ATI and nVIDIA - so there are two different kinds of drivers to read temperature from. I'm interested in learning how to do it for each different card driver.
Language in question is irrelevant - it could be C/C++, .NET platform, Java, but let's say that .NET is preferred.
Anyone been doing this before?
For nVidia you would use nvcpl.dll.
Here's the documentation:
http://developer.download.nvidia.com/SDK/9.5/Samples/DEMOS/common/src/NvCpl/docs/NVControlPanel_API.pdf
I found this: AMD Display Library SDK (ADL for short). That covers ATI cards.
http://developer.amd.com/display-library-adl-sdk/
Link to the original page, via Wayback Machine:
http://web.archive.org/web/20101103020811/http://developer.amd.com/gpu/adlsdk/Pages/default.aspx