Stochastic computing (SC) is a promising technique for applications that require low area overhead and fault tolerance, but can tolerate relatively high latency. In the SC paradigm, logical computation is performed on randomized bit streams. In prior work, streams were generated with linear feedback shift registers; these contributed heavily to the hardware cost and consumed a significant amount of power. This paper introduces a new approach for encoding signal values: computation is performed on analog periodic pulse signals. Exploiting pulse width modulation, time-encoded signals corresponding to specific values are generated by adjusting the frequency and duty cycles of pulse width modulated (PWM) signals. With this approach, the latency, area, and energy consumption are all greatly reduced. Experimental results on image processing applications show up to 99% performance speedup, 98% saving in energy dissipation, and 40% area reduction compared to prior stochastic approaches. Circuits synthesized with the proposed approach can work as fast and energy-efficiently as a conventional binary design while retaining the fault-tolerance and low-cost advantages of conventional stochastic designs.
|Original language||English (US)|
|Number of pages||14|
|Journal||IEEE Transactions on Very Large Scale Integration (VLSI) Systems|
|State||Published - May 2017|
Bibliographical noteFunding Information:
This work was supported by the National Science Foundation under Grant CCF-1408123.
- Energy-efficient computing
- mixed-signal design
- pulse width modulation
- stochastic computing (SC) circuits
- stochastic number generator (SNG)
- time-encoded values