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Roland Grinis 95d2b5b8d9 initial build		2021-06-27 22:12:02 +01:00
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src	initial build	2021-06-27 22:12:02 +01:00
build.gradle.kts	initial build	2021-06-27 22:12:02 +01:00
README.md	initial build	2021-06-27 22:12:02 +01:00

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 it locally:

./gradlew -q :kmath-noa:publishToMavenLocal