<p>There is a ton of neuromorhpic hardware being pumped out these days. Off the top of my head, I can name <a href="http://www.research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml#fbid=WCIDcTXRNC3" rel="nofollow">IBM</a> (BlueGene and TrueNorth), <a href="http://www.technologyreview.com/news/520211/qualcomm-to-build-neuro-inspired-chips/" rel="nofollow">Qualcomm</a>, <a href="http://web.stanford.edu/group/brainsinsilicon/neurogrid.html" rel="nofollow">Neurogrid</a>, Brainstorm (Neurogrid 2.0), <a href="http://www.artificialbrains.com/spinnaker" rel="nofollow">Spinnaker</a>, (questionably) <a href="http://higherintelligencebook.com/" rel="nofollow">Peter van der Made's chip</a>, <a href="http://www.artificialbrains.com/brainscales" rel="nofollow">BrainScaleS</a>, in addition to various FPGA and VLSI implementations that I've come across.</p>

<p>However, has there been an extensive comparison of these various hardware approaches and their usefulness/extensibility?</p>

<p>For an example of the comparison I'm looking for, Spinnaker can run Nengo (a brain simulation software based on the NEF), while Peter's chip doesn't run software, thus I would claim that Spinnaker is more useful than Peter's. I would assume (naively) that IBMs TrueNorth chip would be somewhere in the middle, since it is programmable, but does not support learning.</p>

CC BY-SA 3.0
2015-04-19T09:41:43.363Z
This seems impossible to answer as written. It might be possible to answer if you narrowed down the set of hardwares to compare to 2-3, or more precisely specified the parameters you want all these compared on.
Christian Hummeluhr
CC BY-SA 3.0
2015-04-19T17:39:25.983Z
@ChristianHummeluhr I agree. I voted to close it (instead of deleting it) until I get time to re-think how best to phrase this question.
Seanny123
<theoretical-neuroscience><neural-network>
Differences between the many versions of neuromorphic hardware
Seanny123
# Differences between the many versions of neuromorphic hardware

(Asked by: username_0 on 2014-09-05)

There is a ton of neuromorhpic hardware being pumped out these days. Off the top of my head, I can name [IBM](http://www.research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml#fbid=WCIDcTXRNC3) (BlueGene and TrueNorth), [Qualcomm](http://www.technologyreview.com/news/520211/qualcomm-to-build-neuro-inspired-chips/), [Neurogrid](http://web.stanford.edu/group/brainsinsilicon/neurogrid.html), Brainstorm (Neurogrid 2.0), [Spinnaker](http://www.artificialbrains.com/spinnaker), (questionably) [Peter van der Made's chip](http://higherintelligencebook.com/), [BrainScaleS](http://www.artificialbrains.com/brainscales), in addition to various FPGA and VLSI implementations that I've come across.

However, has there been an extensive comparison of these various hardware approaches and their usefulness/extensibility?

For an example of the comparison I'm looking for, Spinnaker can run Nengo (a brain simulation software based on the NEF), while Peter's chip doesn't run software, thus I would claim that Spinnaker is more useful than Peter's. I would assume (naively) that IBMs TrueNorth chip would be somewhere in the middle, since it is programmable, but does not support learning.

**Tags:** theoretical-neuroscience, neural-network

> **Comments:**
> **username_1**: This seems impossible to answer as written. It might be possible to answer if you narrowed down the set of hardwares to compare to 2-3, or more precisely specified the parameters you want all these compared on.  
> **username_0**: @ChristianHummeluhr I agree. I voted to close it (instead of deleting it) until I get time to re-think how best to phrase this question.  

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## 0 answers

