I have two basic questions about getting started with GPGPU programming:
(1) If I do GPGPU on my Mac, will it affect the image on the monitor? How do I know the windowing system or other programs output is not competing for the GPU?
(2) Is there a way to try out AMD GPU programming somewhere without buying a high-end graphics card? The rental cloud places I have seen all use Nvidia. My computation would be logical integer (bit-twiddling) compute-bound, and I have read that AMD GPU is better for these applications.
1) It won't affect the image on the monitor. And to check if another process is using the GPU you'll need something like AMD System Monitor for mac (this application only works on Windows)
2) Any radeon HD 4xxx and above supports OpenCL (previous card might support this, but I'm not sure). This mean any new AMD card you can buy, including the cheapest ones support OpenCL.
The difference between the expensive cards and the cheap ones is the number of stream processors. For example
Radeon HD 4350: 80 stream processors
Radeon x290: 2560 stream processors
Related
I'm starting OpenCL. As I've understood, a platform is a vendor-specific OpenCL implementation, and a device is a processing unit that can be used by a platform.
I've made a simple C++ code that prints the platform name and for each of its devices prints the device name, and its output is
Platform 0: Intel(R) OpenCL HD Graphics
Device 0: Intel(R) Gen9 HD Graphics NEO
Platform 1: Intel(R) CPU Runtime for OpenCL(TM) Applications
Device 0: Intel(R) Core(TM) i5-6200U CPU # 2.3GHz
My question is, shouldn't I expect the two devices to be under the same platform? Given I have a laptop, and the GPU is integrated together with the processor. Also, will this then forbid me for assigning both GPU and CPU devices to the same context? (which I've read has some memory sharing advantages)
shouldn't I expect the two devices to be under the same platform
Only if the vendor provides a platform with drivers for both those devices. I'm not sure if Intel's "NEO" platform has also CPU driver, but i'm pretty sure the "CPU runtime" only has driver for the CPU, not the iGPU. You'll have to list the devices of each platform to find out.
will this then forbid me for assigning both GPU and CPU devices to the same context
You have to list the devices - if NEO has both devices then you can use that. But you can't have devices from different platforms in a single context.
Can Intel Xeon Phi be configured to receive data direct from FPGA board, process them and send result to host memory?
I have large flow of input data and don't want to have redundant transfers (FPGA board ->Host Memory->MIC->Host Memory) over PCI. I want more elegant scheme (FPGA board-> MIC->Host Memory) Is it possible?
In case you don't know, this question was posted and it receives some comments at Intel Many Integrated Core Architecture Forum https://software.intel.com/en-us/forums/topic/540368
Is there a possibility to exclusively reserve the GPU for an OpenCL host programme?
No other process shall have access to this device via OpenCL or OpenGL.
Background is that my software calculates real time data on the GPU and therefore it's not good for the performance if the GPU is doing other stuff as well.
My laptop had
- one CPU core i5: Intel(R) Core(TM) i5-3210M CPU # 2.50GHz
- one Graphic card: Intel(R) HD Graphics 4000
- one Nvidia card ( external card ): GeForce GT 630M
But When I tried to use JavaCL.createBestContext(), it looks like just use one card Intel HD Graphics. So I tried to combine 3 : CPU and 2 GPUs by using:
List<CLDevice> devices = new ArrayList<CLDevice>();
// try to list all platform and devices
for(CLPlatform platform : JavaCL.listPlatforms()) {
//System.out.println(platform.getName());
for (CLDevice device : platform.listAllDevices(true)) {
System.out.println(device.getName().trim());
devices.add(device);
}
}
CLDevice device1 = (CLDevice)devices.get(0);
CLDevice device2 = (CLDevice)devices.get(1);
CLDevice device3 = (CLDevice)devices.get(2);
CLContext context = JavaCL.createContext(null, device1, device2, device3);
But I got error when try to use 3 at the same. So How can compile CPU and GPUs in JavaCL ? Because I read that OpenCL is standard to support parallel programming by using CPU and GPU. So If I miss something, please let me know. Any idea or answers will be appreciated.
Thanks,
Duy.
Sadly, its not that easy. When creating a single context across multiple devices, the devices all have to come from the same platform. Creating a context containing the Intel CPU and GPU should work, but the Nvidia GPU has to be in its own context (different platform, Nvidia not Intel).
Here's how I handle this scenario: I create a context for each device and a thread for each context. Each thread takes a portion of the data I'm working on and dispatches it to its assigned OpenCL device. This way, you can mix, CPUs, GPUs from both AMD and Nvidia, and any other hardware that comes along.
Its important to do load balancing across the threads so that you don't have faster devices sitting idle waiting for a slower device to catch up.
I have installed NVidia graphics card on my notebook, which supports Optimus technology (second graphics card is integrated on the Intel processor).
Suppose, I am with my notebook on AC adapter forever (or at least 99% of my work with notebook) - is there any advantage of preferring optimus option over discrete graphics card?
Yes, you will consume less electricity and thus pay less on your provider :)
On some laptops, it also enable the CPU to run at full speed, while it's not the case when the discrete GPU is activated (due to global thermal profile).