{"id":19855813,"url":"https://github.com/ray-chew/tensor-train-decomposition","last_synced_at":"2025-02-28T21:41:29.259Z","repository":{"id":228363917,"uuid":"139103025","full_name":"ray-chew/tensor-train-decomposition","owner":"ray-chew","description":"A short look at tensor-train decomposition with the Xerus library","archived":false,"fork":false,"pushed_at":"2018-06-29T05:10:50.000Z","size":24,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-01-11T13:54:35.122Z","etag":null,"topics":["cpp","tensor-decomposition","tensor-train","xerus"],"latest_commit_sha":null,"homepage":"","language":"C++","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/ray-chew.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,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2018-06-29T05:03:32.000Z","updated_at":"2024-03-19T12:51:15.000Z","dependencies_parsed_at":"2024-03-18T12:58:33.951Z","dependency_job_id":"8ac5df92-b6f2-416d-9bb1-8f977c7e1961","html_url":"https://github.com/ray-chew/tensor-train-decomposition","commit_stats":null,"previous_names":["ray-chew/ttd","ray-chew/tensor-train-decomposition"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Ftensor-train-decomposition","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Ftensor-train-decomposition/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Ftensor-train-decomposition/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Ftensor-train-decomposition/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ray-chew","download_url":"https://codeload.github.com/ray-chew/tensor-train-decomposition/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241245642,"owners_count":19933296,"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":["cpp","tensor-decomposition","tensor-train","xerus"],"created_at":"2024-11-12T14:13:46.588Z","updated_at":"2025-02-28T21:41:29.220Z","avatar_url":"https://github.com/ray-chew.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"A simple benchmarking of calculations involving a tensor-train decomposition (TTD) against a simple-tensor. This is \nbased on the Xerus library[1], and on the nearest-neighbour interaction system (NNIS) example [published \nhere](https://libxerus.org/cascade/), and mentioned in-depth in the paper by Gelß et. al.[2].\n\n* *nnis.cxx* is the TTD example. The complete source code is published on the [Xerus \nwebsite](https://libxerus.org/cascade/).\n\n* *nnis_noTT.cxx* is my attempt at using the Xerus library to solve the simple-tensor format of the same system.\n* The accuracy are similar. See *plot_noTT_long.pdf* or, for the TT-format vs the simple-tensor,  \n    Residual: 0.00134 vs 0.00133,  \n    Norm:  0.976103 vs 0.976128.\n    \n* However, the TTD calculations are about 500 times faster.\n\n    |\u0026nbsp; | TT-format| simple-tensor|\n    | ---- | :----: | :----: |\n    | Run 1 | 1.751 | 874.2 | \n    | Run 2 | 1.568 | 887.6 |\n    | Run 3 |  1.550 | 911.4 |\n    | **Avg. time** |  **1.623s** | **891.1s** |\n    \n* The advantage of the tensor-train decomposition for large arrays is significant.\n\n\n*References*:  \n[1] Huber, B. \u0026 Wolf, S. Xerus - A General Purpose Tensor Library. *https://libxerus.org*, (2014–2018).  \n[2] Gelß, P., Klus, S., Matera, S., \u0026 Schütte, C. Nearest-Neighbor Interaction Systems in the Tensor-Train Format. *Journal of Computational Physics 341*, (2017), 140-162.  \n[3] Oseledets, I. V. Tensor-Train Decomposition. *SIAM Journal on Scientific Computing 33*, 5 (2011), 2295-2317.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fray-chew%2Ftensor-train-decomposition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fray-chew%2Ftensor-train-decomposition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fray-chew%2Ftensor-train-decomposition/lists"}