Neuromorphic Computer Design To Be Simulated on Supercomputer

Wednesday, April 8, 2015

Neuromorphic Computer Design To Be Simulated on Supercomputer

Neuromorphic Computing
Researchers will explore the design and potential of next-generation supercomputers that incorporate a highly efficient neuromorphic processor, which more closely represents the human brain in its architectural design. 

For brain-inspired computing to become a reality, the underlying hardware must become sufficiently powerful to do in-silicon what the brain does naturally. One of the important advances in this field was the 2014 debut of the first neuromorphic chip, TrueNorth, developed by IBM with funding from DARPA.

Now, a new project has been announced that will further explore the technology. As part of the “Massively Parallel Modeling and Simulation of Next-Generation Hybrid Neuromorphic Supercomputer Systems,” researchers at the Rensselaer Polytechnic Institute will address the potential for the neuromorphic processor to incorporated into a next-generation supercomputer.

With a grant from the Air Force Research Laboratory, the Rensselaer team will use the institute’s supercomputer, Amos, to run a massively parallel simulation of proposed neuromorphic supercomputer designs. The model will also enable them to examine various network designs and assess the machine’s suitability for compute- and data-intensive science and engineering problems.

The researchers are looking to test the feasibility of building a hybrid supercomputer that uses both neuromorphic and conventional processors. The mixed-processor approach been growing in popularity ever since Roadrunner broke the petaflops barrier in 2008 with AMD x86 CPUs and souped-up IBM Cell co-processors.

TrueNorth Neuromorphic Chip

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This is a simulation and will not use the actual TrueNorth hardware, the researchers will base the model on IBM’s specifications for the processor and its simulation development kit.

"The question we’re asking is: What if future supercomputer designs were to have several embedded neuromorphic processors?"

“The question we’re asking is: What if future supercomputer designs were to have several embedded neuromorphic processors?” said Christopher Carothers, director of the Center for Computational Innovations, in the official announcement. “How would you design that computer? And what new capabilities would it offer?”

The simulation will also incorporate a series of learning algorithms specific to the incorporation of the neuromorphic chip, said James Hendler, director of the Rensselaer Institute for Data Exploration and Applications (IDEA).

One of the primary advantages of the brain’s computational ability is its speed and efficiency. Computers that rely on neuromorphic processing are expected to use far less energy and emit less heat than conventional chips. They will also excel at classification problems, like pattern recognition and dealing with error messages.

The TrueNorth architecture supports very fast parallel computing that is naturally fault-tolerant. The chip incorporates 5.4 billion transistors arranged in a network of 4,096 neurosynaptic cores, yielding the equivalent of one million neurons and 256 million synapses.

“We’re actually using a supercomputer to simulate another supercomputer that doesn’t even exist,” said Carothers. “It’s a great use of supercomputing technology because we can take advantage of its power to run accurate simulations at a finer, more granular level than can be built.”

SOURCE  Rensselaer Polytechnic Institute

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