cross-posted from: https://programming.dev/post/8391233

Dr. Chris Rackauckas (@chrisrackauckas@fosstodon.org) writes:

#julialang GPU-based ODE solvers which are 20x-100x faster than those in #jax and #pytorch? Check out the paper on how #sciml DiffEqGPU.jl works. Instead of relying on high level array intrinsics that #machinelearning libraries use, it uses a direct kernel generation approach to greatly reduce the overhead.

Read Automated translation and accelerated solving of differential equations on multiple GPU platforms

  • ericjmorey@programming.devOPM
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    8 months ago

    Your submission in “GPU-based ODE solvers which are 20x-100x faster than those in #jax and #pytorch” was removed for Testing functions using new Proton UI.