[Eeglablist] Installing CUDAICA on Windows 10 (2021 update)

Makoto Miyakoshi mmiyakoshi at ucsd.edu
Thu Nov 11 09:56:04 PST 2021


Dear John,

Thank you for your comment.
It was difficult for me partly because I'm not very experienced in building
an environment, and also because of recent changes in the dependent
softwares between May 2019 and Nov 2011.

   1. Microsoft updated Intel Parallel Studio XE to oneAPI which made a
   critical part in Ugo's suggestions no longer valid.
   2. I did not find 'C:\Users\Ugo\AppData\Local\Programs\Microsoft VS
   Code\bin' just by following Ugo's suggestions. I found that
installing Microsoft
   Visual Studio Code is necessary in my case, which may be due to Microsoft's
   update on Windows Visual Studio (but probably this is not a part of
   requirements.)

Ugo posted his solution only 2.5 years ago. Yesterday, I spent 10 hours to
make it work, which shows fow fast technology is left behind time. And it
is not because the technology becomes obsolete but because it becomes a
lost technology due to software updates.

> We use the 48core computers for the runica, but it does not appear to
profit from the multiple CPUs.

You'll definitely benefit from running AMICA using all the cores! It may
not be as fast as CUDAICA, but AMICA has some nice extra features including
auto data rejection, time-series data of model's log likelihood, etc.

Makoto

On Wed, Nov 10, 2021 at 10:14 PM Richards, John <RICHARDS at mailbox.sc.edu>
wrote:

> Re CUDAICA.  I was able to install it, i don't remember it being that
> difficult.  I had to mess around with the CUDA version.
>
> I have found it "blazing" fast compared to runica. I have not timed it.
> We have 10-15 min sessions with EGI 128, 250 hz, do the Prep pipeline to
> get avg ref, and then CUDAICA.  It takes < 5 min to do the Prep, and  < 5
> min to do the CUDAICA; cf 45 min to 60 min with runica.  I may not be using
> the most recent runica.   BTW, we have fairly powerful computers; we use 48
> cores for the Prep pipeline which is a vast speedup, and V100's with 16gb
> or 32gb.   Definitely not bargain chips.  We use the 48core computers for
> the runica, but it does not appear to profit from the multiple CPUs.  The
> Prep pipeline also is very slow on single CPUs, but very fast on the 48 CPU
> machines.
>
> I would be glad to share more details if anyone is interested.
>
> John
>
>
> ***********************************************
> John E. Richards
> Carolina Distinguished Professor
> Department of Psychology
> University of South Carolina
> Columbia, SC  29208
> Dept Phone: 803 777 2079
> Fax: 803 777 9558
> Email: richards-john at sc.edu
>
> https://urldefense.proofpoint.com/v2/url?u=https-3A__jerlab.sc.edu&d=DwIFAw&c=-35OiAkTchMrZOngvJPOeA&r=pyiMpJA6aQ3IKcfd-jIW1kWlr8b1b2ssGmoavJHHJ7Q&m=Huri_n6jWh8zdcR4owEEJ4-OCWk3Tuhb-lZ4bO5ZmEPVSvmQwaK_oBMvCoL8R4J1&s=eEYNpj01sEGAM90ppVv06ny9mss5jBeptXZmxzGMfIg&e=
> *************************************************
>
> -----Original Message-----
> From: eeglablist <eeglablist-bounces at sccn.ucsd.edu> On Behalf Of Makoto
> Miyakoshi via eeglablist
> Sent: Thursday, November 11, 2021 1:02 AM
> To: EEGLAB List <eeglablist at sccn.ucsd.edu>; ugob at siu.edu
> Subject: [Eeglablist] Installing CUDAICA on Windows 10 (2021 update)
>
> Dear list members,
>
> I summarized the steps to install cudaica() which uses GPU computation to
> calculate infomax ICA (Raimondo et al., 2012). The result from the speed
> comparison between runica() and cudaica() was not as dramatic as x25
> reported by the original paper, probably because Tjerk's smart hack alone
> already gave x4-5 speed up to runica(). Still, using a relatively cheap
> GTX1660 (the pre-COVID price range is $250), I confirmed x4-5 speed up
> compared with runica(). The detailed instruction can be found in the
> following link.
>
>
> https://sccn.ucsd.edu/wiki/Makoto%27s_useful_EEGLAB_code#By_using_CUDAICA_.2811.2F10.2F2021_added.29
>
> WARNING: The installation was difficult.
>
> Makoto
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