Asynchronous Logic: Ready For It?

prostoalex writes "For a while academia and R&D labs explored the possibilities of asynchronous logic. Now Bernard Cole from Embedded.com tells us that asynchronous logic might receive more acceptance than expected in modern designs. The main advantages, as article states, are 'reduced power consumption, reduced current peaks, and reduced electromagnetic emission', to quote a prominent researcher from Philips Semiconductors. Earlier Bernard Cole wrote a column on self-timed asynchronous logic."

Comments

Re:What's wrong with synchronous?

[Junks Jerzey]

From what I've understood, in most aspects of computing, synchronous data communication is preferable. IE, network cards, sound-cards, printers, etc. Don't better models support bi-directional synchronous communication?

You're just talking about I/O. Of course I/O has to be synchronous, because it involves handshaking.

I think there are some general misconceptions about what "asynchronous" means. Seriously, all I'm seeing are comments from people without a clue about chip design, other than what they read about at arstechnica.com or aceshardware.com. And if you don't know anything about the *real* internals of synchronous chips, then how can you blast asynchronous designs?

So-called asynchronous processors have already been designed and prototyped. Chuck Moore's recent (as in "ten years old") stack processors are mostly asynchronous, for example. Most people are only familiar with the x86 line, and to a lesser extent the PowerPC, and a much, much lesser extent the Alpha and UltraSPARC. Unless you've done some research into a *variety* of processor architectures, please refrain from commenting. Otherwise you come across like some kind of "Linux rules!" weenie who doesn't have a clue what else is out there besides (Windows, MacOS, and UNIX-variants).

What if?

[bunyip]

I'm sure that many /. readers, like me, are wondering if asynchronous chips get faster if you pour liquid nitrogen on them.

Seriously though, does the temperature affect the switching time? Or does the liquid nitrogen trick just prevent meltdown of an overclocked chip?

Re:Some further information

[JayBat]

Those of us that have been around the block more than twice know that asynchronous design has been the technology of the future for a long, long time. My personal experience goes back to the mid-seventies, but I'm sure there were asynch he-men doing their thing with vacuum tubes and RTL. :-)

The catch, then as now, is that asynch logic is just plain more difficult for our tiny little human brains to grok. This was true back in the days when humans designed their own logic, and it is even more true now when 99%+ of all logic is designed not by humans, but by logic synthesis software (Synopsys DC and Cadence PKS).

That said, there are always folks out there doing Cool Stuff w/asynch circuits. Hope that Ivan Sutherlands's group at Sun Labs survives Sun's recent massive layoffs.

Re:Kurzweil

[pclminion]

I've had this argument many times. First, there's lots of evidence that biological brains are heavily chaotic, which ANNs traditionally are not. Second, brains are extremely recurrent in ways that could never be simulated by traditional computers -- there are simply too many links. Third, the human brain is not based merely on reward and punishment. When I sit in a chair at night, pondering whether I agree or not with what Bush has done today, there's no clear source of reward or punishment. Yet, at the end of the day, my brain has changed. ANNs have no ability to self-contemplate and change in this way.

Fourth, when an ANN is trained, every weight in the network is changed. In a biological brain, particular links form and are destroyed, but learning is not a global process. I'm not a neuroscientist, so if I'm wrong, someone please point that out.

Fifth, you can ask a human why he/she came to a particular conclusion. You can't ask an ANN why it reached a particular conclusion. Sometimes, analysis is possible on smaller networks. But for multi-layer networks with thousands of hidden units, this becomes impossible. I really don't think it's a question of computational power. I have a deep sense that somehow, biobrains are fundamentally different from their mathematical cousins.

I won't claim that ANNs have no place in thinking machines. But having worked with them extensively, I feel that, although they are extremely valuable computational tools, they are not a magic wand. Many pattern recognition and data organization tasks can be much better performed by traditional symbolic algorithms.