6,925 research outputs found
On Timing Model Extraction and Hierarchical Statistical Timing Analysis
In this paper, we investigate the challenges to apply Statistical Static
Timing Analysis (SSTA) in hierarchical design flow, where modules supplied by
IP vendors are used to hide design details for IP protection and to reduce the
complexity of design and verification. For the three basic circuit types,
combinational, flip-flop-based and latch-controlled, we propose methods to
extract timing models which contain interfacing as well as compressed internal
constraints. Using these compact timing models the runtime of full-chip timing
analysis can be reduced, while circuit details from IP vendors are not exposed.
We also propose a method to reconstruct the correlation between modules during
full-chip timing analysis. This correlation can not be incorporated into timing
models because it depends on the layout of the corresponding modules in the
chip. In addition, we investigate how to apply the extracted timing models with
the reconstructed correlation to evaluate the performance of the complete
design. Experiments demonstrate that using the extracted timing models and
reconstructed correlation full-chip timing analysis can be several times faster
than applying the flattened circuit directly, while the accuracy of statistical
timing analysis is still well maintained
Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding
The vicinity of phase transitions selectively amplifies weak stimuli,
yielding optimal sensitivity to distinguish external input. Along with this
enhanced sensitivity, enhanced levels of fluctuations at criticality reduce the
specificity of the response. Given that the specificity of the response is
largely compromised when the sensitivity is maximal, the overall benefit of
criticality for signal processing remains questionable. Here it is shown that
this impasse can be solved by heterogeneous systems incorporating functional
diversity, in which critical and subcritical components coexist. The subnetwork
of critical elements has optimal sensitivity, and the subnetwork of subcritical
elements has enhanced specificity. Combining segregated features extracted from
the different subgroups, the resulting collective response can maximise the
tradeoff between sensitivity and specificity measured by the
dynamic-range-to-noise-ratio. Although numerous benefits can be observed when
the entire system is critical, our results highlight that optimal performance
is obtained when only a small subset of the system is at criticality.Comment: 7 pages, 4 figure
Anomalous scaling and Lee-Yang zeroes in Self-Organized Criticality
We show that the generating functions of avalanche observables in SOC models
exhibits a Lee-Yang phenomenon. This establishes a new link between the
classical theory of critical phenomena and SOC. A scaling theory of the
Lee-Yang zeroes is proposed including finite sampling effects.Comment: 33 pages, 19 figures, submitte
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