Yes, that's the essence of it. If you implement TP the straightforward way,
you need to loop over each segment in each cell to see which cells should
be in predictive state. With this optimization you just visit those
segments that have some activity.

As far as the pseudo code in the whitepaper, this strategy by itself is
just a code optimization trick. The end result should be identical to the
pseudo code, but you will get it faster.

--Subutai


On Thu, Sep 19, 2013 at 8:40 AM, Marek Otahal <[email protected]> wrote:

> As I understand it, instead of computing new values for each column/cell
> (as the brain does, because it's totally local and parallel), we would
> compute only those cells where some bit changed and is 1 (this requires we
> have links: "input bit"-to what cells), since only 2% are on in a SDR, this
> is the 50x.
> ..or I'm completely wrong :)
>
> Cheers, Mark
>
>
> On Thu, Sep 19, 2013 at 4:13 PM, Oreste Villa <[email protected]>wrote:
>
>> Hi all,
>>
>> I am trying to make sense to the following comment that I got a couple of
>> weeks ago from Subutai regarding 50x speedup on the new algorithm for
>> the TP.
>>
>> This is the comment:
>>
>> "TP is inherently slower and it was more challenging to optimize it. In
>> the TP now rather than iterating over all the cells we iterate over all the
>> ON input bits. The end result is identical but since we have about 2%
>> sparsity in input bits, the latter method is about 50x faster. After
>> optimizations, the SP and TP are now at roughly the same level in timing
>> profiles. When the TP is more "full" of segments it becomes slower than SP
>> again."
>>
>> Is there anybody available to explain how to exactly fit this into the
>> white-paper pseudocode for the TP?
>>
>> In return, if I understand it enough and the topic comes up,
>> I volunteer to help writing the "white paper 2.0" :-)
>>
>> Thanks,
>>
>> Oreste
>>
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>>
>>
>
>
> --
> Marek Otahal :o)
>
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>
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