I see claims of performance improvements in latest driver release notes - yet I for one am not seeing any significant performance increases of late - may be 5-10% at most since last several upgrades. I have been running “ai-benchmark” suite - I see score of 15k for RTX 0270 on WSL2 vs 25k on Linux. Similarly In my real-world pattern-matching application - WSL2 is much slower than Linux on same hardware (RTX 5000).
I can accept 5-10% slowness but 40% is just too much. What is ultimate goal of Nvidia WSL2 Driver effort? To be competitive w/ Linux? Any hope if we are going to get there soon?
Thank you for your reply! I installed the latest Kernel and indeed there is an impressive jump of 33% in performance (my 2070 RTX now reports 20k in ai-benchmark vs 15k before. WSL is now just 20% behind Windows or Linux (24-25k range for this card). This is very impressive. Please keep us posted. It will be nice if the gap got to within 5-10%.
Benchmark I am running is called Tensorflow Ai-benchmark (its a quick 10 min benchmark see: https://ai-benchmark.com/ for more) Its not the most rigorous benchmark but it its quick and good enough I would say.
I am not sure if Hardware Scheduling was on before but I ran same benchmark making sure Hardware Scheduling was on and this time it WSL2 came within 4% of Windows.
WDDM Windows Ai-Benchmark Score for Super 2070: 22433
WDDM WSL2 Ubuntu Ai-Benchmark Score for Super 2070: 21548 (4% less)
TCC mode for Quadro cards like my RTX 5000 gets you another 5-7% but WSL driver only virtualizes in WDDM mode . SO its fair to say its likely no more than 10% slower vs WIndows even when Windows is run TCC mode and WSL in WDDM mode.
I am now going to run same benchmark on Linux (same machine same NVME drive - in dual boot mode)
I also have some longer heavy duty OpenCV template matching jobs (that runs 2-4 hrs on multiple GPUs - quite intensive) and some faster rcnn models that run much longer. So more results coming.