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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