[Eeglablist] Hardware recommendations

[Makoto Miyakoshi]

Dear Malte,

Let me summarize our communication outside the list for others.

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> CPU utilization is ~40% during the process, RAM utilization is 100% (so
100% of the 32 Gb are used)

I suggest you try the following solution.

   - Use the following optional inputs: 'cycles', [3 10], 'freqs', [1 45],
   'nfreqs', [50], 'timesout', 6849 This should set your sliding window size
   to 3380 ms or something like that, which should produce 6849 time point
   i.e., about 1 time point per second.

The most alarming sign was 'Using 3 cycles at lowest freq to 25600 at
highest' 25600 cycles sounds crazy. If you use the above parameters, it
will be up to 10.

Makoto

On Mon, Jan 13, 2020 at 11:20 PM Malte Anders <malteanders at gmail.com> wrote:

> Hi everybody,
>
> I have collected huge amounts of EEG data with 512 Hz sampling frequency
> and 34 electrodes.
>
> For one subject (~2-3 hours of data), a simple Time/Frequency decomposition
> between 1 and 40 Hz with standard settings calling the newtimef function
> takes approx. 8 hours for 1 hour of recorded data on my Computer (4790k, 32
> Gb of DDR3 Ram, Intel HD GPU), so 16-24 hours for one dataset in total.
> This is simply too long as I am currently working alone on this. CPU
> utilization is ~40% during the process, RAM utilization is 100% (so 100% of
> the 32 Gb are used).
>
> I would like to invest in new hardware (I am also considering used
> hardware) with a price point around 1500-3000€. Which would make more
> sense:
> -A new Ryzen 3950x, 16 cores with 128 Gb of DDR4 RAM (2666 Mhz) ~ 1500€
> -A used workstation, e.g. with Dual CPU: 2 x 12 core Xeon E52670v3 and 256
> Gb RAM ~ used approx. 2200€
>
> The Xeon has more cores, but way lower clock speed. It does have double the
> amount of RAM though.
>
> Would you recommend a dedicated GPU (Nvidia?) for this?
>
> Any recommendations are greatly appreciated. Thanks!
> Malte
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