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Gpu shark version check
Gpu shark version check






gpu shark version check gpu shark version check
  1. Gpu shark version check code#
  2. Gpu shark version check zip#

GPU Shark 0.12.0 brings the support of NVIDIA GeForce RTX 2080 Ti, RTX 2080 and RTX 2070 GPUs.

Gpu shark version check zip#

It would have been nice to see that 80% of the execution time was spent on console IO. Download GPU Shark 0.12.0.0 (portable / zip archive) Release Notes. (It didn't help that VS2012 refused to profile my CUDA app. So, my advice would be to disable any console IO, and see if or how that affects things. It looks like NVVP is buffering everything, and displaying it in a separate thread, or just saving a bunch of output until some threshold is reached, when it adds that buffer to its own console tab. It appears that NVVP's mechanism for buffering or processing that output has significantly less overhead than allowing the operating system to handle it directly. NVVP has to redirect stdout to its own internal buffer in order to capture the application's output (which it shows in its console tab). Of course, this could also be handled in a separate CPU thread if that sort of overhead is unacceptable in your circumstances. Instead, it was printing the status message for every frame, and the console IO became the bottleneck.īy only printing the status message every 100 frames (though the optimal number here would depend on your application), the frame rate jumped back up to match what I was seeing in NVVP. I had intended for this to only happen about once every 100-200 frames.

gpu shark version check

The cause appears to be a status message I was printing to the console via cout. Namely: my app achieved between 9 frames (synchronous launches) per second when running under NVVP, but around 100-120 when running outside of the profiler. This is an old question, but I've just finished chasing the same issue (though the cause may not be the same). In Visual Profiler that figure goes down to ~100MB. When run off command line, task manager indicates usage of 650-700MB of memory (spikes at the first cudaFree(0) call). Moreover, far less memory is used with Visual Profiler.However, GPU usage was reported at 0.0% when run with Visual Profiler, but went as high as 98% when run off command line.GPU-shark indicated that my performance state was unchanged at P0 when I switched from command line to Visual Profiler.

Gpu shark version check code#

all required code has been run in both cases. I have checked that the calculated output on command line and Visual Profiler is identical - i.e.Incidentally, there's been a noticeable slowdown in compiled code on my machine very recently, even old code that previously ran quickly, hence I'm getting suspicious. So the natural question is why? Is there something wrong with command line, or does Visual Profiler do something different and not really execute everything as on the command line? A piece of code that takes well over 1 minute on the command line was done in a matter of seconds in NVIDIA Visual Profiler (running the same.








Gpu shark version check