Learning, probabilistic, and asynchronous technologies for an ultra efficient datapath
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A novel microarchitecture and circuit design techniques are presented for an asynchronous datapath that not only exhibits an extremely high rate of performance, but is also energy efficient. A 0.5 um chip was fabricated and tested that contains test circuits for the asynchronous datapath. Results show an adder and multiplier design that due to the 2-dimensional bit pipelining techniques, speculative completion, dynamic asynchronous circuits, and bit-level reservation stations and reorder buffers can commit 16-bit additions and multiplications at 1 giga operation per second (GOPS). The synchronicity simulator is also shown that simulates the same architecture except at more modern transistor nodes showing adder and multiplier performances at up to 11.1 GOPS in a commerically available 65 nm process. When compared to other designs and results, these prove to be some of the fastest if not the fastest adders and multipliers to date. The chip technology also was tested down to supply voltages below threshold making it extremely energy efficient. The asynchronous architecture also allows more exotic technologies, which are presented. Learning digital circuits are presented whereby the current supplied to a digital gate can be dynamically updated with floating gate technology. Probabilistic digital signal processing is also presented where the probabilistic operation is due to the statistical delay through the asynchronous circuits. Results show successful image processing with probabilistic operation in the least significant bits of the datapath resulting in large performance and energy gains.