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Neuromorphic computation shows tremendous promise as a complementary paradigm to conventional computer architecture. To realize this potential, neuromorphic devices will have to carve out a unique niche in the computational landscape. Compute Me is dedicated to exploring this problem, as well as the technical issues that must be overcome on the way.

Understanding the Competition

Ben Chandler | February 8, 2010

Cache Memory In About SyNAPSE I characterized neuromorphic devices as the opposite of conventional Von Neumann processors. This is somewhat of a oversimplification, however. Modern processors are actually quite evolved from pure Von Neumann devices. They are dramatically more capable on virtually every computational workload than their heritage would suggest is possible. For neuromorphic devices to find any success in the marketplace, they’ll need to offer a significant performance gain against existing solutions, but with comparable or lesser power consumption and cost.

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We all need control (theory)

Tim Barnes | February 7, 2010

Top Gun taught us that the best and brightest pilots can perform some amazing aerobatics.  Nobody seems surprised that a good pilot, with some practice, can move seamlessly from the flight maneuvers used on a Boeing 747 to those featured in Blue Angels shows.  While computer autopilots have performed well in commercial aircraft for some time, however, getting an electronic computer to pull a plane successfully through an aerobatic maneuver is almost impossible, and is thus a relatively new field of research. Read the rest of this entry »

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Biophys-Ed, Compute Me, DARPA SyNAPSE
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Why simulating a cat when we can simulate a human (or even more!)

Massimiliano Versace | November 26, 2009

eugenebrainWhen I read (and wrote about) the recent controversy between Modha and Markram, I had this inescapable déjà vu feeling….weird, where did I hear that somebody already simulated a “brain” of the scale of the human brain? Of course!…. Eugene Izhikevich, a very bright (and VERY funny) neuroscientist that, in 2007, visited our center CELEST. During that visit, he showed what at that time (in 2005, and may be up to today) was one of the “largest scale” neural simulation. Read the rest of this entry »

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Cat fight over blue brain

Massimiliano Versace | November 24, 2009

cat_fightIn my recent post, I commented on IBM’s announcement at the Supercomputing Conference (SC09) in Portland, Ore., that they had simulated a brain with the number of neurons and synapses present in a cat’s brain. It looks like the controversial statement of IBM being finally able to “simulate a cat’s brain” (or however their original statements has been distorted) has been stirring some more comments. Henry Markram, the leader of the Blue Brain project at EPFL, Lausanne, sent an open letter to IBM CTO Bernard Meyerson, along with several media (UK Daily Mail, Die Zeit, Wired, Discover, Forbes). One big question is: was Modha’s statement somehow distorted? Did he actually simply claim that IBM simulated a system that has the same number of neurons of a cat, as opposed to simulate “the cat’s brain?”. This is an important distinction. Anyway, Neurdons must know, so here it is! Enjoy!

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The subtle difference between simulating brains and number of cells

Massimiliano Versace | November 19, 2009

091019122647-largeIEEE Spectrum has published an interesting article titled “IBM Unveils a New Brain Simulator: A big step forward in a project that aims for thinking chips”. The post describes IBM’s Almaden Research Center latest simulation effort announced at the Supercomputing Conference (SC09), where they unveiled that “that they have created the largest brain simulation to date on a supercomputer. The number of neurons and synapses in the simulation exceed those in a cat’s brain; previous simulations have reached only the level of mouse and rat brains.” Read the rest of this entry »

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Reliable Computation with Biological Components

Ben Chandler | February 25, 2009
Feinerman et al. Figure 1b: logic components fabricated from hippocampal neurons

Feinerman et al. Figure 1b: logic components fabricated from hippocampal neurons

Neuromorphic technology is a young field, with little in the way of established paradigms or techniques. Most of the recent related work, however, focuses on silicon implementation of neural-inspired mechanisms. Feinerman et al. buck the trend and build reliable computation devices using actual neurons.

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