# PSDEstimator using multiple cores even when n\_jobs=1 **URL:** \ **Category:** Mailing List Archive (read-only)\ **Tags:** list-archive\ **Created:** [July 2, 2018, 11:51am UTC](https://mne.discourse.group/t/psdestimator-using-multiple-cores-even-when-n-jobs-1/1560 "2018-07-02T11:51:15Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [July 2, 2018, 11:51am UTC](https://mne.discourse.group/t/psdestimator-using-multiple-cores-even-when-n-jobs-1/1560/1 "2018-07-02T11:51:15Z")
External Email - Use Caution Hi all, I found a problem in mne.decoding.PSDEstimator.transform() method. In short, it does not respect the attribute "n\_jobs". This problem does not exist in MNE 0.14 and only exists in MNE 0.15 and above. I tested only on stable versions. Normally, I restrict the PSD estimation to use a single core (n\_jobs=1) because there are many other time-critical processes running together in the system. In MNE 0.15 and above, the transform() function uses up to 4 cores equivalent (over 50% total usage on an 8-core system). This is in contrast with the same function in MNE 0.14, where only 1 core is used as expected. The following minimal code replicates the problem. import numpy as npimport mneimport time mne.set\_log\_level('WARNING') psde = mne.decoding.PSDEstimator(sfreq=512, fmin=1, fmax=40, n\_jobs=1) iterations = 1000 w = np.random.rand(1, 64, 256)print('Start %d iteratinos' % iterations) t\_start = time.time()for i in range(iterations):     psd = psde.transform(w)print('Took %.3f seconds' % (time.time() - t\_start)) In Windows 10 Pro with i7-4790K CPU (8 logical cores), I ran the above code 5 times each with 1000 computations. In the idle period, the cpu usage was maximum 3%. \*Results\* - mne 0.14: CPU usage 17% (equivalent to approx. 1 core = 12.5%) 10.461, 10.755, 10.861, 10.843, 10.636 seconds. Average: 10.711s per 1000 computations. - mne 0.15, 0.16: CPU usage 56% (equivalent to approx. 4 cores = 50%) 11.608, 10.737, 10.734, 11.283, 10.909 seconds. Average: 11.054s per 1000 computations. So, I don't see much difference in computation time but the CPU usage was 4x higher in MNE 0.15 and above. It seems to me that there's a bug in PSDEstimator class that always prefers to use multiple cores even when n\_jobs=1, causing a lot of overhead by forced multiprocessing. Please have a look and fix this issue. Thanks! Best, Kyuhwa Lee -------------- next part -------------- An HTML attachment was scrubbed... URL: [http://mail.nmr.mgh.harvard.edu/pipermail/mne\_analysis/attachments/20180702/bc5b70df/attachment.html](http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20180702/bc5b70df/attachment.html) ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [July 3, 2018, 8:59pm UTC](https://mne.discourse.group/t/psdestimator-using-multiple-cores-even-when-n-jobs-1/1560/2 "2018-07-03T20:59:41Z")
External Email - Use Caution hi Kyuhwa, even with n\_jobs=1 if you use a multithreaded linear algebra library like MKL or openblas you will use more than 1 core. to prevent this you should read about the environment variable : OMP\_NUM\_THREADS HTH Alex