Youtube Video (5 minutes and 16 seconds) describing my team’s work in the context of IBM’s Cognitive Systems Era: http://www.youtube.com/watch?v=gQ3HEVelBFY
Archives for 2012
Building on recently published cognitive computing chip technology, this week at ASYNC 2012: IEEE International Symposium on Asynchronous Circuits and Systems Cornell-IBM team published a new paper that won the Best Paper Award.
TITLE: A Digital Neurosynaptic Core Using Event-Driven QDI Circuits
AUTHORS: Nabil Imam, Filipp Akopyan, John Arthur, Paul Merolla, Rajit Manohar, Dharmendra S Modha
ABSTRACT: We design and implement a key building block of a scalable neuromorphic architecture capable of running spiking neural networks in compact and low-power hardware. Our innovation is a configurable neurosynaptic core that combines 256 integrate-and-fire neurons, 1024 input axons, and 1024×256 synapses in 4.2mm2 of silicon using a 45nm SOI process. We are able to achieve ultra-low energy consumption 1) at the circuit-level by using an asynchronous design where circuits only switch while performing neural updates; 2) at the core-level by implementing a 256 neural fanout in a single operation using a crossbar memory; and 3) at the architecture level by restricting core-to-core communication to spike events, which occur relatively sparsely in time. Our implementation is purely digital, resulting in reliable and deterministic operation that achieves for the first time one-to-one correspondence with a software simulator. At 45pJ per spike, our core is readily scalable and provides a platform for implementing a wide array of real-time computations. As an example, we demonstrate a sound localization system using coincidence-detecting neurons.
Recently, Science published a very interesting article:
ABSTRACT: The structure of the brain as a product of morphogenesis is difficult to reconcile with the observed complexity of cerebral connectivity. We therefore analyzed relationships of adjacency and crossing between cerebral fiber pathways in four nonhuman primate species and in humans by using diffusion magnetic resonance imaging. The cerebral fiber pathways formed a rectilinear three-dimensional grid continuous with the three principal axes of development. Cortico-cortical pathways formed parallel sheets of interwoven paths in the longitudinal and medio-lateral axes, in which major pathways were local condensations. Cross-species homology was strong and showed emergence of complex gyral connectivity by continuous elaboration of this grid structure. This architecture naturally supports functional spatio-temporal coherence, developmental path-finding, and incremental rewiring with correlated adaptation of structure and function in cerebral plasticity and evolution.
Interesting fragments from the paper:
"Geometrically, this configuration is highly exceptional … This sheet structure was found throughout cerebral white matter and in all species, orientations, and curvatures. Moreover, no brain pathways were observed without sheet structure."
"Grid structure should restrict and simplify axonal path-finding compared with models that allow less constrained and less correlated connectivity within and between cerebral areas."
"Thus, the grid organization of cerebral pathways may represent a "default connectivity," on which adaptation of structure and function can both occur incrementally in evolution and development, plasticity, and function."
January 27, 2012 issue of Science published a very interesting NEWSFOCUS on "What It’ll Take To Go Exascale". Here is the abstract:
To accurately simulate global climate, researchers will need supercomputers more powerful than any yet designed. These so-called exascale computers would be capable of carrying out 10^18 floating point operations per second, or an exaflops. That’s nearly 100 times more powerful than today’s biggest supercomputer, Japan’s "K Computer," which achieves 11.3 petaflops (1015 flops), and 1000 times faster than the Hopper supercomputer. The United States now appears poised to reach for the exascale, as do China, Japan, Russia, India, and the European Union. Advances in supercomputers have come at a steady pace over the past 20 years, enabled by the continual improvement in computer chip manufacturing. But this evolutionary approach won’t cut it in getting to the exascale. Instead, computer scientists must first figure out ways to make future machines far more energy efficient and tolerant of errors, and find novel ways to program them.