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I was so excited to dive into this, but ended up with the same Takeaway as most other commenters. Aside: As a data scientist, I’ve been surprised how much I’ve
by orzig 8y ago
I was so excited to dive into this, but ended up with the same Takeaway as most other commenters. Aside: As a data scientist, I’ve been surprised how much I’ve needed to learn about the finer points of optimizing GPU utilization for training.
It has all been from more experienced coworkers, and I would much appreciate any resources anybody could point me to (free or paid) so that I could round out my knowledge
- dragontamer 8y agoLearn enough about GPUs to be able to read the profiler. That should be your #1 goal: learning to use the profiler and performance counters. The profiler not only tells you how fast your code is, but also why your code is fast or slow... at least to the best ability of the hardware performance counters. Is it RAM-bottlenecked? Is it Compute bound? Are your Warps highly utilized? Etc. etc. If you don't know what the profiler is saying, then study some more. https://docs.nvidia.com/nsight-visual-studio-edition/Content/Analysis/Report/CudaExperiments/KernelLevel/PerformanceCounters.htm https://docs.nvidia.com/nsight-visual-studio-edition/Content...