- #Rocm vs opencl benchmark driver
- #Rocm vs opencl benchmark software
- #Rocm vs opencl benchmark code
- #Rocm vs opencl benchmark series
PlaidML is a OpenCL v1.2 ML libary but does not conform to my previous 'v1.2 and CUDA' rant. This has allowed (i think this is the reason anyway) TensorFlow to be built ontop of MIOpen soįor those of you that aren't aware FaceSwap uses PlaidML for AMD and TensorFlow for Nvidia. In short HIP is cuda clone designed to allow easy migration from CUDA, perform a find+replaceįrom 'cudaFunction()' to 'hipFuntion()' and you're 90% done.
#Rocm vs opencl benchmark software
Part of this software stack is MIOpen, a low-level ML libary and a new runtime API "HIP". In the attempt to catch up they have built the Radeon Open Compute stack What i did, whether is was based on false pretenses or not.ĪMD has been trying to catch up in the ML game, how well they are doing is something you canĭecide for yourself. It doesn't matter though, i'm mearly explaining why i belived I was a very ignorant observation and I'm sure there's someone reading this than knows farīetter than I and can say why this is.
![rocm vs opencl benchmark rocm vs opencl benchmark](https://www.phoronix.com/data/img/results/amd_780g_linux/06.png)
Now i do not know what the benefits of migrating from OpenCL v1.2 to v2.0+ are if thier are any atĪll. With Nvidia OpenCL, but would then also have a seperate CUDA path. That a program would be written in OpenCL v1.2, what looked to me as a way of staying compatible My belief came from looking at software requirements, CUDA or OpenCL.ĭue to Nvidia pushing CUDA for the past 10+ years they stopped thier OpenCL support at v1.2, whileĪMD and Intel continued to support up to v2.2 and v2.0 respectively. Jen-Hsun Huang stated 10 years ago that Nvidia is a To CUDA, which shouldn't surprise anyone. What i do mean is that the entire software stack is biased
#Rocm vs opencl benchmark code
The code i looke at was very easy to follow. I do not mean that the developers have done a 'bad' job of coding, i think FaceSwap is excellent and RTX GPUs aside, i was very much in the belief that this was a software rather than a hardware issue. To some people who cannot / do not wish to buy another GPU. What i already knew, the comparison in performace as terrible. Looking at the forums i saw multipule posts that essentially summed I have just started looking at DeepFakes and ML and have an AMD GPU, a position im sure people The code i've written is not the best and would require some cleanup before anybody programming This was done purely as an 'I wonder if'.
![rocm vs opencl benchmark rocm vs opencl benchmark](https://i.imgur.com/novy87Q.png)
Nvidia is the king of ML, this isn't me attempting to deny that.
#Rocm vs opencl benchmark series
More graphics and benchmarks for the Radeon RX 6800 series will be available on Phoronix shortly.This was a small project by myself, a non-expert in either Python or Machine Learing (ML).
#Rocm vs opencl benchmark driver
On the Radeon side were the RX 5700, RX 5700 XT, Radeon VII, RX 6800, and RX 6800 XT from the 8.45pm driver that offered OpenCL 2.0 support.Ī series of OpenCL calculation benchmarks for these tests were carried out today via the Phoronix Test Suite. As mentioned in the previous article, NVIDIA didn’t submit an RTX 3070/3090 graphics cards to Phoronix for Linux testing, so no points of comparison today, but hopefully the other amp parts soon. On the NVIDIA side was the NVIDIA 455.38 Linux driver, which has OpenCL 1.2 support, and it tested GeForce RTX 2080, RTX 2080 SUPER, RTX 2080 Ti, TITAN RTX, and RTX 3080. There are also the various open sources -Projects like CLSPV for the execution of OpenCL kernels on Vulkan, but these are also in an early stage … In contrast to the OpenGL / Vulkan AMD Linux driver and the numerous realizable options, the ROCm OpenCL path is currently the de -facto solution and far less confusing for Linux consumers.) (Well, there is OpenCL support via Clover Gallium3D as well, but that is still a work in progress and it lacks OpenCL image support, among other things … And it is not officially supported by AMD. The only OpenCL support option currently is the ROCm-based OpenCL code path, which is included in the packet driver and presumably soon in the open source ROCm repository. While there are multiple driver options for AMD Radeon GPUs when it comes to OpenGL / Vulkan support on Linux, as discussed in the previous article, luckily there is no such driver fragmentation on the OpenCL side.
![rocm vs opencl benchmark rocm vs opencl benchmark](https://www.phoronix.com/data/img/results/sapphire_hd4550/10.png)
7 s good to see that it works well together for Big Navi.