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Deep learning inference-as-a-service tools and pipelines for gravitational wave physics

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fastmachinelearning/gw-iaas

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GW-IAAS

DOI

NOTE FOR HERMES USERS: HERMES DEVELOPMENT HAS PERMANENTLY MOVED TO THIS REPOSITORY.

WIP repository for the code used to implement the experiments in Hardware-accelerated Inference for Real-Time Gravitational-Wave Astronomy. Original code used for the paper is being restructured into a more organized and general-purpose set of tools which will be made available here.

Structure

libs contains the various libraries used to construct inference-as-a-service pipelines.

projects contains pipelines built using the libraries in libs, as well as simpler examples for usage and a Jupyter Notebook slideshow covering the work.

Prerequisites

Built on top of Poetry, which is required to run. Most pipelines will also require a user-managed Google Cloud service account key for deploying clients and services on cloud resources.

Additional steps will be required for each of the various pipelines, please consult their individual READMEs. Libraries in libs will be available on PyPi sometime in the near future.