{"id":24493036,"url":"https://github.com/fastmachinelearning/gw-iaas","last_synced_at":"2025-04-14T01:40:36.838Z","repository":{"id":37253835,"uuid":"393513577","full_name":"fastmachinelearning/gw-iaas","owner":"fastmachinelearning","description":"Deep learning inference-as-a-service tools and pipelines for gravitational wave physics","archived":false,"fork":false,"pushed_at":"2022-07-01T16:10:45.000Z","size":10846,"stargazers_count":2,"open_issues_count":10,"forks_count":4,"subscribers_count":13,"default_branch":"main","last_synced_at":"2025-03-27T15:52:14.479Z","etag":null,"topics":["deep-learning","gravitational-waves","inference","ml-infrastructure"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/fastmachinelearning.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-08-06T22:01:32.000Z","updated_at":"2023-03-13T01:14:37.000Z","dependencies_parsed_at":"2022-09-03T07:41:39.985Z","dependency_job_id":null,"html_url":"https://github.com/fastmachinelearning/gw-iaas","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fgw-iaas","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fgw-iaas/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fgw-iaas/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fastmachinelearning%2Fgw-iaas/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fastmachinelearning","download_url":"https://codeload.github.com/fastmachinelearning/gw-iaas/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248809039,"owners_count":21164893,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","gravitational-waves","inference","ml-infrastructure"],"created_at":"2025-01-21T19:18:57.366Z","updated_at":"2025-04-14T01:40:36.819Z","avatar_url":"https://github.com/fastmachinelearning.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# GW-IAAS\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5567703.svg)](https://doi.org/10.5281/zenodo.5567703)\n\n_NOTE FOR HERMES USERS: HERMES DEVELOPMENT HAS PERMANENTLY MOVED TO [THIS REPOSITORY](https://github.com/ML4GW/hermes)._\n\nWIP repository for the code used to implement the experiments in [Hardware-accelerated Inference for Real-Time Gravitational-Wave Astronomy](https://arxiv.org/abs/2108.12430). 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.\n\n## Structure\n`libs` contains the various libraries used to construct inference-as-a-service pipelines.\n\n`projects` contains pipelines built using the libraries in `libs`, as well as simpler examples for usage and a Jupyter Notebook slideshow covering the work.\n\n## Prerequisites\nBuilt on top of [Poetry](https://python-poetry.org), which is required to run. Most pipelines will also require a user-managed Google Cloud [service account key](https://cloud.google.com/iam/docs/creating-managing-service-account-keys#creating_service_account_keys) for deploying clients and services on cloud resources.\n\nAdditional 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.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffastmachinelearning%2Fgw-iaas","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffastmachinelearning%2Fgw-iaas","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffastmachinelearning%2Fgw-iaas/lists"}