Stochastic number generator (SNG) is one important component of stochastic computing (SC). An SNG usually consists of a random number source (RNS) and a probability conversion circuit (PCC). The SNGs occupy a large portion of the total area and power of a stochastic circuit. Thus, it is critical to lower the area and power of the SNGs. The existing methods only focused on simplifying the RNSs inside the SNGs, such as sharing the RNSs and using emerging devices. However, how to reduce the area and power of PCCs is never studied. In this work, we explore this problem and propose a solution that can effectively reduce the area and power of PCCs. We also study the theoretical limit on the cost of SNG and find that our proposed design approaches the limit. The experimental results show that our design can gain up to 2x improvement in power-delay product over the traditional SNGs.
|Original language||English (US)|
|Title of host publication||Proceedings - 2018 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2018|
|Publisher||IEEE Computer Society|
|Number of pages||6|
|State||Published - Aug 7 2018|
|Event||17th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2018 - Hong Kong, Hong Kong|
Duration: Jul 9 2018 → Jul 11 2018
|Name||Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI|
|Other||17th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2018|
|Period||7/9/18 → 7/11/18|
Bibliographical noteFunding Information:
This work is supported in part by National Natural Science Foundation of China (NSFC) under grant no. 61472243 and 61204042 and in part by National Science Foundation (NSF) of U.S.A. under grant no. CCF-1408123 and CCF-1438286. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSFC and NSF.
© 2018 IEEE.
- Probability Conversion Circuit
- Stochastic number generator
- Theoretical Limit