High-performance cellular automata random number generators for embedded probabilistic computing systems

Shackleford, Barry; Tanaka, Motoo; Carter, R.J.; Snider, Greg

doi:10.1109/eh.2002.1029885

Cited by 12 publications

(14 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The f avg-max of the frequency mix was set approximately to 100 MHz. To switch the control, three types of number sequences were evaluated: (1) linear sequence, (2) LFSR based random number [9] and (3) cellular automata based random number sequences [11]. The sampling distribution characteristics of pseudo random clocks were studied for 1GHz, 622.08MHz, 500MHz, 300MHz and 250MHz signals.…”

Section: Experimental Setup and Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Standard cell based pseudo-random clock generator for statistical random sampling of digital signals

Bhatti

Chugg

Draper

2007

2007 50th Midwest Symposium on Circuits and Systems

View full text Add to dashboard Cite

Abstract-A statistical random sampling technique has recently emerged as an elegant design-time efficient technique to address many timing issues of on-chip signals. To obtain reliable measurement results, it requires uniformly distributed sampling edges within the interval defined by the periodic cycles of the signal under measurement. This paper analyzes the characteristics of a random sampling clock relative to the signal under measurement and provides design rules for synthesis of pseudo-random sampling clocks. The proposed circuit provides a way to mix a range of frequencies in a pseudo-random fashion to produce uniformly distributed edges for random sampling, which yields measurement accuracy very close to that of true random sampling. A practical circuit design technique of pseudo-random clock generation is proposed based on a standard cell approach. This allows on-chip integration of a random clock generator while keeping the overall system design-time efficient and portable across varying technologies. The proposed designs are targeted to IBM Cu-08 standard cell libraries and provide a measurement resolution of 1ps.

show abstract

Section: Experimental Setup and Resultsmentioning

confidence: 99%

“…In this work we compare three types of switching sequences: (1) linear sequence, (2) LFSR based random number [9] and (3) cellular automata based random number sequences [11].…”

Section: ) Pseudo Random Clock Produced By Frequency MIXmentioning

confidence: 99%

Standard cell based pseudo-random clock generator for statistical random sampling of digital signals

Bhatti

Chugg

Draper

2007

2007 50th Midwest Symposium on Circuits and Systems

View full text Add to dashboard Cite

show abstract

“…The random mechanism employs the greedy approach as a backbone, but it allows for overwriting of paths if the probability of caching that path (as obtained from a random number generator) is greater than a certain threshold. 32-bit non-local and asymmetrical cellular-automata CA25443 was used as a random number generator because it passed more empirical randomness tests, displayed large cycle length [7] and allowed efficient implementation.…”

Section: Quality Of Paths Optimizationmentioning

confidence: 99%

Performance Evaluation of Probe-Send Fault-tolerant Network-on-chip Router

Mediratta

Draper

2007

2007 IEEE International Conf. On Application-Specific Systems, Architectures and Processors (ASAP)

View full text Add to dashboard Cite

show abstract

“…In [1], Barry et al expanded the neighborhood size to four and introduced a nonlocal neighborhood connection scheme. They found a number of 64-cell 1-D CA PRNGs passing DIEHARD through exhaustive searching.…”

Section: A 1-and 2-d Ca Prngsmentioning

confidence: 99%

2-D CA Variation With Asymmetric Neighborship for Pseudorandom Number Generation

Guan

Shu

Quieta

2004

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

View full text Add to dashboard Cite

High-performance cellular automata random number generators for embedded probabilistic computing systems

Cited by 12 publications

References 18 publications

Standard cell based pseudo-random clock generator for statistical random sampling of digital signals

Standard cell based pseudo-random clock generator for statistical random sampling of digital signals

Performance Evaluation of Probe-Send Fault-tolerant Network-on-chip Router

2-D CA Variation With Asymmetric Neighborship for Pseudorandom Number Generation

Contact Info

Product

Resources

About