Has anyone investigated implementimg neural nets in FPGAs?
Neural Networks in FPGA
Started by ●April 9, 2005
Reply by ●April 9, 20052005-04-09
No, no-one has. That's why when you put 'neural nets fpga' into Google, you get no hits whatsoever. Apart from the first 10000, that is. Syms. "e" <e@yahoo.com> wrote in message news:WKudnX4QIdcO9sXfRVn-ig@adelphia.com...> Has anyone investigated implementimg neural nets in FPGAs?
Reply by ●April 10, 20052005-04-10
On Sat, 9 Apr 2005 18:17:18 -0700, "Symon" <symon_brewer@hotmail.com> wrote:>No, no-one has. That's why when you put 'neural nets fpga' into Google, you >get no hits whatsoever. Apart from the first 10000, that is. >Syms.More importantly, has anybody found a use for neural nets? John
Reply by ●April 10, 20052005-04-10
"John Larkin" <jjlarkin@highNOTlandTHIStechnologyPART.com> wrote in message news:iudh5191obt8jj1g9rd44j8h4e1kd8jq3a@4ax.com...> On Sat, 9 Apr 2005 18:17:18 -0700, "Symon" <symon_brewer@hotmail.com> > wrote: > >>No, no-one has. That's why when you put 'neural nets fpga' into Google, >>you >>get no hits whatsoever. Apart from the first 10000, that is. >>Syms. > > > More importantly, has anybody found a use for neural nets? > > John > >I use mine daily....
Reply by ●April 10, 20052005-04-10
Tryin to avoid some gardening work I had to check that out. I only see upto p76 so 760 of 9880 refs. Even after turning off a redundancy warning it goes to 980 out of 11600 so I guess the other 9-10k can't be reached or can they? Is it possible to random access out there in the 9880 boonies, I don't usually go further than 1st few pages. And google says it won't go past 1000. Hint directly type in over "num=300" to jump but 1000 gate still there. Anyway to save the whole thing to file in 1 go? (after change settings to 100 items per page) johnjakson at usa dot com
Reply by ●April 10, 20052005-04-10
On Sat, 09 Apr 2005 22:21:59 -0700, John Larkin <jjlarkin@highNOTlandTHIStechnologyPART.com> wrote:>On Sat, 9 Apr 2005 18:17:18 -0700, "Symon" <symon_brewer@hotmail.com> >wrote: > >>No, no-one has. That's why when you put 'neural nets fpga' into Google, you >>get no hits whatsoever. Apart from the first 10000, that is. >>Syms. > > >More importantly, has anybody found a use for neural nets? > >John >Yes, I've very likely that the letter you receive are sorted by zip code using a neural nets. That's only one example in a million others Nick
Reply by ●April 10, 20052005-04-10
OK - Let me rephrase my question. Has anyone who frequents this newsgroups and has a lot of experience with FPGAs, actually tried to make a functioning NN system and has some realworld experience with FPGA NN Systems. (Mean as it may sound , this is meant to rule out present or past graduate students that only got as far simulation.) JJ wrote:> Tryin to avoid some gardening work I had to check that out. > > I only see upto p76 so 760 of 9880 refs. > > Even after turning off a redundancy warning it goes to 980 out of 11600 > so I guess the other 9-10k can't be reached or can they? > > Is it possible to random access out there in the 9880 boonies, I don't > usually go further than 1st few pages. And google says it won't go past > 1000. Hint directly type in over "num=300" to jump but 1000 gate still > there. > > Anyway to save the whole thing to file in 1 go? > (after change settings to 100 items per page) > > > johnjakson at usa dot com >
Reply by ●April 10, 20052005-04-10
More likely than not, most regulars here probably have not dipped their finger into NNs as they are probably busy more in DSP, or embedded space. But google fpga neural networks on the web did highlight at least a couple of may be interesting articles for you to start with. Those authors may or may not have been here too but AFAIK I haven't seen NN come up that often. google groups too to see where they hang out regards johnjakson
Reply by ●April 11, 20052005-04-11
e wrote:> Has anyone investigated implementimg neural nets in FPGAs?Many (most?) classical neural networks utilise non-linear functions at the nodes, with fractional synapse weights and so on. In SW implementations, floating point is the order of the day. Add in the back-propagation training algorithms and you have significant non-integer arithmetic to contend with. For implementation in commodity FPGA HW, this will all hurt. Fixed point will help, but bring similar precision issues that arise in DSP. Perhaps there is research on pure digital neural networks (binary weights, logical and/or/xor node functions) etc? Dig around in the evolvable hardware research literature, they've been banging on it for years. It is my expectation (not experience), that there will be significant practical issues in implementing reasonable sized classical NNs on FPGA hardware. You will very quickly find yourself building either huge arrays of FPGAs, or diving into dynamic reconfig / multicontext FPGA territory to get the logic coverage required to implement what will be a very large (virtual) circuit. Or, implement a couple of NN nodes in your FPGA fabric, with some sort of controller updating the weights and accumulating responses at each node. Use this to simulate the entire massive (and parallel) NN operation. Surprise surprise it's time/area trade. Lots of fun no doubt, but not trivial either. John
Reply by ●April 11, 20052005-04-11
Take a look at GenoByte, http://www.genobyte.com/cbm.html. News is old though, ca. 2000. -- Pete e wrote:> Has anyone investigated implementimg neural nets in FPGAs?
