Stochastic sequential machine synthesis with application to constrained sequence generation-Reference-Cited by-同舟云学术

Stochastic sequential machine synthesis with application to constrained sequence generation

Published:2000-07 Issue:3 Volume:5 Page:658-681
ISSN:1084-4309
Container-title:ACM Transactions on Design Automation of Electronic Systems
language:en
Short-container-title:ACM Trans. Des. Autom. Electron. Syst.

Author:

Marculescu Diana¹,Marculescu Radu²,Pedram Massoud³

Affiliation:

1. Univ. of Maryland, College Park

2. Univ. of Minnesota, Minneapolis

3. Univ. of Southern California, Los Angeles

Abstract

In power estimation, one is faced with two problems: (1) generating input vector sequences that satisfy a given statistical behavior (in terms of signal probabilities and correlations among bits); (2) making these sequences as short as possible so as to improve the efficiency of power simulators. Stochastic sequential machines (SSMs) can be used to solve both problems. In particular, this paper presents a general procedure for SSM synthesis and describes a new framework for sequence characterization to match designers' needs for sequence generation or compaction. Experimental results demonstrate that compaction ratios of 1–3 orders of magnitude can be obtained without much loss in accuracy of total power estimates.

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications

Link

https://dl.acm.org/doi/pdf/10.1145/348019.348566

Reference22 articles.

1. Markov Chains as Random Input Automata

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cycle-Based Decomposition of Markov Chains With Applications to Low-Power Synthesis and Sequence Compaction for Finite State Machines;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2006-12

2. A Markov Chain Sequence Generator for Power Macromodeling;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2004-07

3. A Markov chain sequence generator for power macromodeling;IEEE/ACM International Conference on Computer Aided Design, 2002. ICCAD 2002.