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new_user55

HN member
Joined
Sat, Dec 03, 2022, 1:55 AM UTC
HN karma
5
Public activity
7 items

About new_user55

Interested in Scientific Computation, Machine Learning, and Applied Mathematics. PhD in Physical Chemistry.

Recent public activity

  1. comment
    Comment #48911696

    You can write the cuda kernels and directly differentiate them using Enzyme. Last time I checked KOKKOS was still WIP: https://github.com/EnzymeAD/Enzyme/issues?q=kokkos

  2. comment
    Comment #48911301

    Really nice work. I love Enzyme, and used it in my project about differentiable atomic descriptors. Idea was that I can quickly gobble up existing C++ and fortran codes alike for a…

  3. comment
    Comment #47852840

    I will guess for linux. Most out of the box linux laptops I saw were intel based. I guess open source support of intel is best among others in the industry. Even in my current thin…

  4. comment
    Comment #47348182

    Its really cool! If you don't mind me asking, does it support variable size inputs? I am bit confused about JAX in that regards. I am trying for long to run JAX stablehlo models in…

  5. comment
    Comment #36871876

    We wanted to use ONNX runtime for a "model driver" for MD simulations, where any ML model can be used for molecular dynamics simulations. Problem was it was way too immature. Like …

  6. comment
    Comment #36871829

    Tinygrad is python only right? Can it provide gradients during C++ runtime as well? ONNX runtime have multiple language backends for inference.

  7. comment
    Comment #33839545

    There is [torch-md]( https://github.com/torchmd/torchmd )