Krishnaswamy, Smita, Markov, Igor L., Hayes, John P.
2013, XII, 124 p.
Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
Presents a comprehensive overview of Logic Circuits
Combines theory with practical examples
Multi-discipline approach to the "hot" topic of uncertainty
Integrated circuits (ICs) increasingly exhibit uncertain characteristics due to soft errors, inherently probabilistic devices, and manufacturing variability. As device technologies scale, these effects can be detrimental to the reliability of logic circuits. To improve future semiconductor designs, this book describes methods for analyzing, designing, and testing circuits subject to probabilistic effects. The authors first develop techniques to model inherently probabilistic methods in logic circuits and to test circuits for determining their reliability after they are manufactured. Then, they study error-masking mechanisms intrinsic to digital circuits and show how to leverage them to design more reliable circuits. The book describes techniques for:
• Modeling and reasoning about probabilistic behavior in logic circuits, including a matrix-based reliability-analysis framework;
• Accurate analysis of soft-error rate (SER) based on functional-simulation, sufficiently scalable for use in gate-level optimizations;
• Logic synthesis for greater resilience against soft errors, which improves reliability using moderate overhead in area and performance;
• Test-generation and test-compaction methods aimed at probabilistic faults in logic circuits that facilitate accurate and efficient post-manufacture measurement of soft-error susceptibility.