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Modal script - benchmarking, profiling and libraries #504
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I won't be able to help you with Modal, but I'll just say that our goal is ultimately to have custom CUDA kernels that outperform cuDNN. So you should, ideally, be able to just run our code without external dependencies. One can dream. :) |
@vyom1611 Hi, I try to run the demo
, but failed. Could you please give me some suggestions? Did I miss some steps? Thank you very much! |
Hi, try running the compile command with the -lcublast option. |
@vyom1611 Thank you very much! It worked after adding the -lcublasLt option.
Have you considered adding support for "ncu"? I tried, but encountered an error and no profile file was generated. |
using ncu is weird, because it likes to profile kernels very deeply. There is a linux_kernel_paranoid level if too high, then nsys cannot profile cpu and os parts during profiling, and for ncu: it seems impossible to fix this on modal containers: And to fix it you have to: Enable access permanently
which seems impossible on modal containers since you need root privilege to edit modprobe.d and create .conf files in /etc/. and even if you managed to change it, then you have to reload modrobe using So currently we cannot run ncu on modal. This is the link for reference: https://developer.nvidia.com/nvidia-development-tools-solutions-err_nvgpuctrperm-permission-issue-performance-counters |
Got it! Thank you! It is a pity since modal offer some free A100 quota :( |
Running the cuda code on modal using the benchmark_on_modal.py script is very useful, but I was wondering if there is a way to install cuDNN onto that app because we cannot run a lot of the faster kernels without libraries like such. Is it also possible to profile using nsight systems on modal?
Using modal is very convenient for people like me who do not have access to gpus, so if we can update the script and add more documentation on how to run profiling and all kinds of kernels on modal, I bet more folks would be able to access and run the codebase.
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