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I found out that solving the ExaModels AC OPF documentation example in a loop results in possible memory leak. All of 6 GB of GPU's VRAM is taken in about 33 solves.
Below is part relevant part of the code and full code to reproduce can be downloaded: gpu memory leak.zip
m = ac_power_model("pglib_opf_case13659_pegase.m",backend=CUDABackend())
for i in 1:50
println(i)
madnlp(m,linear_solver=MadNLPGPU.CuCholeskySolver)
end
GPU memory usage is not necessarily optimized on MadNLP. Curious if this is CuCholeskySolver's issue or general MadNLP issue. Have you tried CUDSSSolver (the default solver for CUDA)?
With package update as suggested in 333 issue, I've managed to run OPF with CUDSSSolver.
I the memory issue is still present. Memory usage goes slowly up with repeated runs of MadNLP until failure due to full VRAM.
I found out that solving the ExaModels AC OPF documentation example in a loop results in possible memory leak. All of 6 GB of GPU's VRAM is taken in about 33 solves.
Below is part relevant part of the code and full code to reproduce can be downloaded: gpu memory leak.zip
Configuration:
Windows,
CPU: AMD R9 5950x
GPU GTX 1060 6GB
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