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The brain-inspired, spike-based neuromorphic system is highly anticipated in the artificial intelligence community due to its high computational efficiency. The recently developed memristor-crossbar-array technology, which is able to efficiently emulate the plasticity of biological synapses and accommodate matrix multiplication, has demonstrated its potential for neuromorphic computing. To facilitate...
As process technology continues scaling down, the memory barrier becomes more severe. Thus, spiking neuromorphic computing that can significantly enhance computing and communication efficiencies has been widely studied. Both conventional CMOS technology and emerging devices have been used in hardware implementation of spiking neuromorphic computing. Particularly, the memristor technology that can...
To minimize the leakage power dissipation of present-day on-chip Decaps, we propose a gated decoupling capacitor (GDecap) technique that deactivates a Decap when it is not needed. The application of the proposed GDecap technique on an eight-way clock-gated clustered pipeline showed that on average, 41.7% Decap leakage power was reduced, with negligible (~ 0.037%) worst-case performance degradation,...
A novel on-chip Decoupling Capacitor (Decap) design - Gated Decoupling Capacitor (GDecap) - is proposed to minimize the leakage power dissipation associated with present-day on-chip decoupling capacitors. Experiments on the application of GDecap in an 8-way clock-gated cluster pipeline show that on average, 41.7% Decap leakage power is improved, with only 0.037% worst-case performance degradation,...
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