[TriEmbed] In need of a tiny, cheap, powerful(ish) computer

[Adam Haile]

I do where I can right now... but numpy is a non-trivial install on some
systems (in my experience). Something not worth it for the majority of
users since most probably don't use more than a couple hundred LEDs, if
that.

I may need to find a way to come up with an optional numpy version...

On Mon, Sep 21, 2015 at 9:45 PM, Carl Nobile <carl.nobile at gmail.com> wrote:

> Adam,
>
> Doing it in pure python may be the issue. Use the numpy package it does
> matrix math extremly fast. If you're flipping pixels around then you will
> get an unbelievable speed increase with numpy.
>
> ~Carl
>
>
> On Mon, Sep 21, 2015 at 9:39 PM, Adam Haile via TriEmbed <
> triembed at triembed.org> wrote:
>
>> It's all CPU. There's usually less than 100MB RAM usage. And yup, 24/7
>> operation.
>> I'm already using nothing but single byte math (with a tiny few float
>> exceptions) and have optimized the heck out of it with a couple of
>> performance profilers. Pretty much it comes down to doing hundreds of
>> thousands of pixel operations per second all in pure python, with no GPU
>> acceleration... this is because my "display" is large LED matrices. So,
>> admittedly, not the best for performance... but I'm also doing way more
>> than users of my library would generally ever try.
>>
>> On Mon, Sep 21, 2015 at 5:01 PM, John Vaughters <jvaughters04 at yahoo.com>
>> wrote:
>>
>>>
>>>
>>> >Forget I mentioned the video thing... Pi is not fast enough regardless.
>>>
>>> Right, so the pi lacks memory and processing power.
>>>
>>> I guess the question is what is your application wanting? Are you
>>> swaping memory? or is the Processor pegged? Or both?
>>>
>>> Do you need 24/7 on time?
>>>
>>> Is it your software that you can change to optimize your system? You
>>> mentioned speed over cores; software changes can possibly fix these
>>> problems.
>>>
>>> Finding sub $150 computers in the x86 family is going to be tough unless
>>> you want a used laptop. But even then, laptops running 24/7 are not the
>>> most reliable.
>>>
>>> I guess my suggestion would be to try to figure out what the hold up is
>>> in your application and system if you want to get the cost to it's lowest.
>>> Or just try the used laptop route.
>>>
>>> John Vaughters
>>>
>>>
>>
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>>
>
>
> --
>
> -------------------------------------------------------------------------------
> Carl J. Nobile (Software Engineer)
> carl.nobile at gmail.com
>
> -------------------------------------------------------------------------------
>
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