{"action":"created","issue":{"url":"https://api.github.com/repos/rtavenar/tslearn/issues/55","repository_url":"https://api.github.com/repos/rtavenar/tslearn","labels_url":"https://api.github.com/repos/rtavenar/tslearn/issues/55/labels{/name}","comments_url":"https://api.github.com/repos/rtavenar/tslearn/issues/55/comments","events_url":"https://api.github.com/repos/rtavenar/tslearn/issues/55/events","html_url":"https://github.com/rtavenar/tslearn/issues/55","id":345625153,"node_id":"MDU6SXNzdWUzNDU2MjUxNTM=","number":55,"title":"Is there a way to parallelise the algorithms?","user":{"login":"tolgamalachi","id":1275311,"node_id":"MDQ6VXNlcjEyNzUzMTE=","avatar_url":"https://avatars3.githubusercontent.com/u/1275311?v=4","gravatar_id":"","url":"https://api.github.com/users/tolgamalachi","html_url":"https://github.com/tolgamalachi","followers_url":"https://api.github.com/users/tolgamalachi/followers","following_url":"https://api.github.com/users/tolgamalachi/following{/other_user}","gists_url":"https://api.github.com/users/tolgamalachi/gists{/gist_id}","starred_url":"https://api.github.com/users/tolgamalachi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tolgamalachi/subscriptions","organizations_url":"https://api.github.com/users/tolgamalachi/orgs","repos_url":"https://api.github.com/users/tolgamalachi/repos","events_url":"https://api.github.com/users/tolgamalachi/events{/privacy}","received_events_url":"https://api.github.com/users/tolgamalachi/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-07-30T06:18:20Z","updated_at":"2018-09-18T15:40:37Z","closed_at":null,"author_association":"NONE","body":"Hello guys,\r\n\r\nfirst of all thanks for this great project!\r\nRight now i am heavily using the k-Shape-Algorithm for clustering (imho) huge amounts of data.\r\nn = 5.000.000, k = 6;8;10;12, m = 56\r\nO(max{n·k ·m· log(m), n·m2, k ·m3}) (complexity of k-Shape from the original paper)\r\n\r\nAnd this takes about 150hours on an Intel(R) Xeon(R) CPU E5-2690 v4 @ 2.60GHz. Sadly the algorithm only uses one core. How can we fix this? How can we make this faster? I am quite new to Python but maybe you have an idea?\r\n\r\nThanks in advance =)"},"comment":{"url":"https://api.github.com/repos/rtavenar/tslearn/issues/comments/422444584","html_url":"https://github.com/rtavenar/tslearn/issues/55#issuecomment-422444584","issue_url":"https://api.github.com/repos/rtavenar/tslearn/issues/55","id":422444584,"node_id":"MDEyOklzc3VlQ29tbWVudDQyMjQ0NDU4NA==","user":{"login":"jlc-christie","id":581275,"node_id":"MDQ6VXNlcjU4MTI3NQ==","avatar_url":"https://avatars0.githubusercontent.com/u/581275?v=4","gravatar_id":"","url":"https://api.github.com/users/jlc-christie","html_url":"https://github.com/jlc-christie","followers_url":"https://api.github.com/users/jlc-christie/followers","following_url":"https://api.github.com/users/jlc-christie/following{/other_user}","gists_url":"https://api.github.com/users/jlc-christie/gists{/gist_id}","starred_url":"https://api.github.com/users/jlc-christie/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jlc-christie/subscriptions","organizations_url":"https://api.github.com/users/jlc-christie/orgs","repos_url":"https://api.github.com/users/jlc-christie/repos","events_url":"https://api.github.com/users/jlc-christie/events{/privacy}","received_events_url":"https://api.github.com/users/jlc-christie/received_events","type":"User","site_admin":false},"created_at":"2018-09-18T15:40:37Z","updated_at":"2018-09-18T15:40:37Z","author_association":"NONE","body":"@tolgamalachi might be worth installing numba and seeing if you can wrap the methods @GillesVandewiele in the `@jit` decorator, e.g. `@jit(nopython=True, parallel=True)`.\r\n\r\nDoesn't always work well but if the function is simple enough it often produces good optimizations with almost no effort. However, the parallel=True argument is an experimental feature according to numba so you might have to look in to the implications of that."}}
{"actor":{"display_login":"jlc-christie"}}