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

Currently, we support only the GNU toolchain for the native artifacts. 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 can simply publish to the local Maven repository:

./gradlew -q :kmath-noa:publishToMavenLocal

This will fetch and build the JNI wrapper jnoa.

In your own application add the local dependency:

repositories {
    mavenCentral()
    mavenLocal()
}

dependencies {
    implementation("space.kscience:kmath-noa:0.3.0-dev-14")
}

To load the native library you will need to add to the VM options:

-Djava.library.path=${HOME}/.konan/third-party/noa-v0.0.1/cpp-build/kmath

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Module kmath-noa

Installation

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