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| how_to [2024/01/24 16:56] – [Analyze multiomicds data?] habil | how_to [2024/01/24 17:14] – [Measure memory used by GPUa?] habil |
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| ==== Measure memory used by GPUa? ==== | ==== Measure memory used by GPUs? ==== |
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| [[http://biggsinstitute.org/neurepiomics-2023/#1686596557113-fac33f90-1709|Neurepiomics]] workshop in 2023: | Use ''torch.cuda.[[https://pytorch.org/blog/understanding-gpu-memory-1/?hss_channel=tw-776585502606721024|memory]]'' , e.g., to discover the effect of clearing gradients at the end of each [[https://towardsdatascience.com/epoch-vs-iterations-vs-batch-size-4dfb9c7ce9c9|iteration]]. With ignite, this can be done using an event handler that calls ''optimizer.[[https://stackoverflow.com/questions/48001598/why-do-we-need-to-call-zero-grad-in-pytorch|zero_grad]](set_to_none=True)''.'' '' |
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| - Shiva's presentation on omics[[https://docs.google.com/presentation/d/1W-pJfPy5MkQscPn5iOSJAkOzuyC2-eirBeHHeKHuYyw/edit#slide=id.p|databases]] | |
| - Mohsen's [[https://docs.google.com/presentation/d/14z2jAkYfmyH6dIH0Rr59ywZk--Kk9ocHzWEDiyd_P4k/edit#slide=id.p|presentation]] for Neurepiomics workshop, 2023-10-09. | |
| - Habil's [[https://docs.google.com/presentation/d/1mGld52Y8TkMXArc5EhcD2XY_0rXvb79BFEgA0YaZwms/edit#slide=id.g63f2c216dd_0_0|slides]] on multiomics data integration. | |
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| ==== Analyze multiomicds data? ==== | ==== Analyze multiomicds data? ==== |
