forked from kscience/kmath
| .. | ||
| src | ||
| build.gradle.kts | ||
| README.md | ||
Module kmath-noa
This module provides a kotlin-jvm frontend for the
NOA
library together with relevant functionality from
LibTorch.
Our aim is to create a Bayesian computational platform
which covers a wide set of applications from particle physics
simulations to deep learning and general differentiable programs
written on top of AutoGrad & ATen.
Installation
Currently, to build native artifacts, 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.
To install the library, simply publish the modules kmath-tensors
and kmath-noa locally:
./gradlew -q :kmath-tensors:publishToMavenLocal :kmath-noa:publishToMavenLocal