forked from kscience/kmath
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src | ||
build.gradle.kts | ||
README.md |
Module kmath-noa
A Bayesian computation library over NOA together with relevant functionality from LibTorch.
Our aim is to cover a wide set of applications from particle physics
simulations to deep learning. In fact, we support any
differentiable program written on top of
AutoGrad
& ATen
.
Installation
To install the library, you can simply publish to the local Maven repository:
./gradlew -q :kmath-noa:publishToMavenLocal
This will fetch and build native artifacts as well.
Currently, we support only
the GNU toolchain. For GPU
kernels, we require a compatible
CUDA
installation. If you are on Windows, we recommend setting up
everything on WSL.