3/22/2023 0 Comments 390 opencl benchmark![]() Nevertheless - even if this is not the limiting factor in performance, it is weird that the GTX 1650 Super performs significantly slower than the RX 570… would anyone suggest how to get more performance from the Nvidia GPU with Darktable? According to this post, it shall be “the upper size limit for any single specific allocation”. options for OpenCL compiler: -w -DNVIDIA_SM_20=1 -DNVIDIA=1 That is a good question. device 0 `GeForce GTX 1650 SUPER' allows GPU memory allocations of up to 977MB device 0 `GeForce GTX 1650 SUPER' supports image sizes of 32768 x 32768 device 0 `GeForce GTX 1650 SUPER' has sm_20 support. Nvidia: opencl library 'libOpenCL.so.1' found on your system and loaded options for OpenCL compiler: -w -DAMD=1 -I"/usr/share/darktable/kernels" device 0 `Ellesmere' allows GPU memory allocations of up to 6565MBĭEVICE_VERSION: OpenCL 1.2 AMD-APP (3143.9) device 0 `Ellesmere' supports image sizes of 16384 x 16384 Has anyone here observed such a low performance with Nvidia GPUs with Darktable on Linux? Would you have some recommendations on how to improve it, maybe also how to trick it to allow it to allocate more memory?īelow are the initial parts of the Darktable logs:ĪMD: opencl library 'libOpenCL.so.1' found on your system and loaded 1/4 of their VRAM for OpenCL memory allocations. And, from the benchmarks that can be found here ( GPU benchmarks in darktable), it seems that Nvidia GPUs often allow only approx. Also, from the log I can see that the Nvidia only allows VRAM allocations only up to 977MB. 30% longer than the older and slower AMD card. However, the results of my tests surprised me - in my experiments, the same set of exports took approx. The OpenCL support worked out of the box. ![]() With the Nvidia GPU, I installed the proprietary nvidia-driver-440. I made some basic setup to compare the cards - I selected 30 edited photos and used darktable-cli to export them while logging the debug and profiling info, also watching the GPU resources and measuring the total duration of the whole operation. So I decided to buy that one as well, keep the better performing one and return the other one. Overall, the 1650 Super shall be better performing GPU, although having only 4GB of VRAM instead of 8GB - but from profiling Darktable exports with the AMD GPU, the VRAM consumption was moving between few hundred of MB up to 2.4GB, therefore I thought 4GB VRAM will be ok. Just few days after byuing the AMD card I found Nvidia GTX 1650 Super on sale. I have used the open source AMD drivers with the necessary OpenCL part installed from the AMDGPU-PRO package. Software-wise, my setup is: Linux Mint 20, Darktable 3.2.1Īt first I bought an AMD RX 570 8GB and got some pretty decent results when compared with processing on CPU only. I decided to build the PC specifically for Darktable and I’m trying to find the best GPU for OpenCL within my budget. ![]() 9003Ġ Compatibility Profile Context 21.4.1 2.112ġ Compatibility Profile Context 21.5.2 3.8013ħ Compatibility Profile Context 15.200.1046.0ĩ Compatibility Profile Context 15.200.1062.1002ĩ Compatibility Profile Context 15.200.1062.1004ĩ Compatibility Profile Context 15.201.1151.0ĩ Compatibility Profile Context 15.201.1151.1007Ħ Compatibility Profile Context 15.300.1025.0ġ Compatibility Profile Context 16.150.0.0ġ Compatibility Profile Context 22.19.662.I would like to kindly ask you for help with issues I’m observing on my new PC build. 1011Ģ Compatibility Profile Context 22.19.128.12Ħ Compatibility Profile Context 20.7.2. GL_AMD_transform_feedback3_lines_trianglesĩ Compatibility Profile Context 15.201.1151.1008Ħ Compatibility Profile Context 15.300.1025.1001ħ Compatibility Profile Context 15.301.1801.1001ġ Compatibility Profile Context 16.150.2211.0ĩ Compatibility Profile Context 21.19.519.2Ħ Compatibility Profile Context 22.19.171.1024ġ Compatibility Profile Context 22.19.662.4ħ Compatibility Profile Context 23.20.780.3ħ Compatibility Profile Context 23.20.782.0ħ Compatibility Profile Context 23.20.788.0Ġ Compatibility Profile Context 19.7.2 1.16003ġ Compatibility Profile Context 19.8.2 1.40003ġ Compatibility Profile Context 19.9.2 3.1007Ħ Compatibility Profile Context 19.12.2 2.61ħ Compatibility Profile Context 20.4.2 9.27017Ħ Compatibility Profile Context 20.5.1.
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