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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, you have to publish locally kmath-core, kmath-tensors with kmath-noa:

./gradlew -q :kmath-core:publishToMavenLocal :kmath-tensors:publishToMavenLocal :kmath-noa:publishToMavenLocal

This builds jtorch a JNI wrapper for NOA/LibTorch, placed inside:

~/.konan/third-party/kmath-noa-<version>/cpp-build