Abstract-Efforts to achieve the long-standing dream of realizing scalable learning algorithms for networks of spiking neurons in silicon have been hampered by (a) the limited scalability of analog neuron circuits; (b) the enormous area overhead of learning circuits, which grows with the number of synapses; and (c) the need to implement all inter-neuron communication via off-chip address-events. In this work, a new architecture is proposed to overcome these challenges by combining innovations in computation, memory, and communication, respectively, to leverage (a) robust digital neuron circuits; (b) novel transposable SRAM arrays that share learning circuits, which grow only with the number of neurons; and (c) crossbar fan-out for efficient on-chip inter-neuron communication. Through tight integration of memory (synapses) and computation (neurons), a highly configurable chip comprising 256 neurons and 64K binary synapses with on-chip learning based on spike-timing dependent plasticity is demonstrated in 45nm SOI-CMOS. Near-threshold, event-driven operation at 0.53V is demonstrated to maximize power efficiency for real-time pattern classification, recognition, and associative memory tasks. Future scalable systems built from the foundation provided by this work will open up possibilities for ubiquitous ultra-dense, ultra-low power brain-like cognitive computers.

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Microprocessor voltage levels include substantial margin to deal with process variation, system power supply variation, workload induced thermal and voltage variation, aging, random uncertainty, and test inaccuracy. This margin allows the microprocessor to operate correctly during worst-case conditions, but during typical conditions it is larger than necessary and wastes energy. We present a mechanism that reduces excess voltage margin by (1) introducing a critical path monitor (CPM) circuit that measures available timing margin in real-time, (2) coupling the CPM output to the clock generation circuit to adjust clock frequency within cycles in response to excess or inadequate timing margin, and (3) adjusting the processor voltage level periodically in firmware to achieve a specified average clock frequency target. We implemented this mechanism in a prototype IBM POWER7 server. During better-than-worst case conditions our guardband management mechanism reduces the average voltage setting 137-152 mV below nominal, resulting in average processor power reduction of 24% with no performance loss while running industry-standard benchmarks.

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