68 research outputs found
Design, Analysis and Test of Logic Circuits under Uncertainty.
Integrated circuits are increasingly susceptible to uncertainty caused by soft
errors, inherently probabilistic devices, and manufacturing variability. As device technologies
scale, these effects become detrimental to circuit reliability. In order to address
this, we develop methods for analyzing, designing, and testing circuits subject to probabilistic
effects. Our main contributions are: 1) a fast, soft-error rate (SER) analyzer
that uses functional-simulation signatures to capture error effects, 2) novel design techniques
that improve reliability using little area and performance overhead, 3) a matrix-based
reliability-analysis framework that captures many types of probabilistic faults, and
4) test-generation/compaction methods aimed at probabilistic faults in logic circuits.
SER analysis must account for the main error-masking mechanisms in ICs: logic,
timing, and electrical masking. We relate logic masking to node testability of the circuit
and utilize functional-simulation signatures, i.e., partial truth tables, to efficiently compute
estability (signal probability and observability). To account for timing masking, we compute
error-latching windows (ELWs) from timing analysis information. Electrical masking
is incorporated into our estimates through derating factors for gate error probabilities. The
SER of a circuit is computed by combining the effects of all three masking mechanisms
within our SER analyzer called AnSER.
Using AnSER, we develop several low-overhead techniques that increase reliability,
including: 1) an SER-aware design method that uses redundancy already present within
the circuit, 2) a technique that resynthesizes small logic windows to improve area and
reliability, and 3) a post-placement gate-relocation technique that increases timing masking by decreasing ELWs.
We develop the probabilistic transfer matrix (PTM) modeling framework to analyze
effects beyond soft errors. PTMs are compressed into algebraic decision diagrams (ADDs)
to improve computational efficiency. Several ADD algorithms are developed to extract
reliability and error susceptibility information from PTMs representing circuits.
We propose new algorithms for circuit testing under probabilistic faults, which require
a reformulation of existing test techniques. For instance, a test vector may need to be
repeated many times to detect a fault. Also, different vectors detect the same fault with
different probabilities. We develop test generation methods that account for these differences, and integer linear programming (ILP) formulations to optimize test sets.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61584/1/smita_1.pd
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