Real-Time Scalable Cortical Computing at 46 Giga-Synaptic OPS/Watt with ~100× Speedup in Time-to-Solution and ~100,000× Reduction in Energy-to-Solution
A. Cassidy, Rodrigo Alvarez-Icaza, Filipp Akopyan, J. Sawada, J. Arthur, P. Merolla, Pallab Datta, Marc González, B. Taba, Alexander Andreopoulos, A. Amir, Steven K. Esser, J. Kusnitz, R. Appuswamy, C. Haymes, B. Brezzo, R. Moussalli, Ralph Bellofatto, C. Baks, M. Mastro, K. Schleupen, C. E. Cox, K. Inoue, S. Millman, N. Imam, E. McQuinn, Yutaka Nakamura, I. Vo, Chen Guok, Don N. Nguyen, S. Lekuch, S. Asaad, D. Friedman, Bryan L. Jackson, M. Flickner, W. Risk, R. Manohar, D. Modha
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引用次数: 83
Abstract
Drawing on neuroscience, we have developed a parallel, event-driven kernel for neurosynaptic computation, that is efficient with respect to computation, memory, and communication. Building on the previously demonstrated highly optimized software expression of the kernel, here, we demonstrate True North, a co-designed silicon expression of the kernel. True North achieves five orders of magnitude reduction in energy to-solution and two orders of magnitude speedup in time-to solution, when running computer vision applications and complex recurrent neural network simulations. Breaking path with the von Neumann architecture, True North is a 4,096 core, 1 million neuron, and 256 million synapse brain-inspired neurosynaptic processor, that consumes 65mW of power running at real-time and delivers performance of 46 Giga-Synaptic OPS/Watt. We demonstrate seamless tiling of True North chips into arrays, forming a foundation for cortex-like scalability. True North's unprecedented time-to-solution, energy-to-solution, size, scalability, and performance combined with the underlying flexibility of the kernel enable a broad range of cognitive applications.