{"action":"opened","issue":{"url":"https://api.github.com/repos/pwollstadt/IDTxl/issues/17","repository_url":"https://api.github.com/repos/pwollstadt/IDTxl","labels_url":"https://api.github.com/repos/pwollstadt/IDTxl/issues/17/labels{/name}","comments_url":"https://api.github.com/repos/pwollstadt/IDTxl/issues/17/comments","events_url":"https://api.github.com/repos/pwollstadt/IDTxl/issues/17/events","html_url":"https://github.com/pwollstadt/IDTxl/issues/17","id":349732189,"node_id":"MDU6SXNzdWUzNDk3MzIxODk=","number":17,"title":"Multi-core?","user":{"login":"EtienneCmb","id":15892073,"node_id":"MDQ6VXNlcjE1ODkyMDcz","avatar_url":"https://avatars3.githubusercontent.com/u/15892073?v=4","gravatar_id":"","url":"https://api.github.com/users/EtienneCmb","html_url":"https://github.com/EtienneCmb","followers_url":"https://api.github.com/users/EtienneCmb/followers","following_url":"https://api.github.com/users/EtienneCmb/following{/other_user}","gists_url":"https://api.github.com/users/EtienneCmb/gists{/gist_id}","starred_url":"https://api.github.com/users/EtienneCmb/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/EtienneCmb/subscriptions","organizations_url":"https://api.github.com/users/EtienneCmb/orgs","repos_url":"https://api.github.com/users/EtienneCmb/repos","events_url":"https://api.github.com/users/EtienneCmb/events{/privacy}","received_events_url":"https://api.github.com/users/EtienneCmb/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-08-11T12:55:10Z","updated_at":"2018-08-11T12:55:10Z","closed_at":null,"author_association":"NONE","body":"Hello !\r\n\r\nYesterday I installed IDTxl and it looks awesome. The documentation and wiki are really nice, especially the description of mTE algorithm. I was playing with the mte example (by the way, [sphinx-gallery](https://sphinx-gallery.readthedocs.io/en/latest/) could be a nice option for your documentation). Example run smoothly, however, on a subset of real data (e.g `(n_processes, n_samples, n_replications)=(6, 1000, 10)`) it started to be really slow and it's almost impossible to test it on my full dataset (`104, 1000, 825` for 17 subjects)\r\n\r\nI want to run it on a super computer, but the multi-core doesn't seems to work. In addition, is there some settings properties so I can set to speed up computations?\r\n\r\nThanx !"}}
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