Empirical derivation of upper and lower bounds of NBTI aging for embedded cores

In deeply scaled CMOS technologies, device aging causes transistor performance parameters to degrade over time. While reliable models to accurately assess these degradations are available for devices and circuits, the extension to these models for estimating the aging of microprocessor cores is not trivial and there is no well accepted model in the literature. This work proposes a methodology for deriving an NBTI-induced aging model for embedded cores. Since aging can only be determined on a netlist, we use an empirical approach based on characterizing the model using a set of open synthesizable embedded cores, which allows us to establish a link between the aging at the transistor level and the aging from the core perspective in terms of maximum frequency degradation. Using this approach, we were able to (1) prove the independence of the aging on the workloads which run by the cores, and (2) calculate upper and lower bounds for the “aging factor” that can be used for a generic embedded processor. Results show that our method yields very good accuracy in predicting the frequency degradation of cores due to NBTI aging effect, and can be used with confidence when the netlist of the cores is not available

Improved Pseudorandom Generators from Pseudorandom Multi-Switching Lemmas

We give the best known pseudorandom generators for two touchstone classes in unconditional derandomization: an $\varepsilon$-PRG for the class of size-$M$ depth-$d$ $\mathsf{AC}^0$ circuits with seed length $\log(M)^{d+O(1)}\cdot \log(1/\varepsilon)$, and an $\varepsilon$-PRG for the class of $S$-sparse $\mathbb{F}_2$ polynomials with seed length $2^{O(\sqrt{\log S})}\cdot \log(1/\varepsilon)$. These results bring the state of the art for unconditional derandomization of these classes into sharp alignment with the state of the art for computational hardness for all parameter settings: improving on the seed lengths of either PRG would require breakthrough progress on longstanding and notorious circuit lower bounds. The key enabling ingredient in our approach is a new \emph{pseudorandom multi-switching lemma}. We derandomize recently-developed \emph{multi}-switching lemmas, which are powerful generalizations of H{\aa}stad's switching lemma that deal with \emph{families} of depth-two circuits. Our pseudorandom multi-switching lemma---a randomness-efficient algorithm for sampling restrictions that simultaneously simplify all circuits in a family---achieves the parameters obtained by the (full randomness) multi-switching lemmas of Impagliazzo, Matthews, and Paturi [IMP12] and H{\aa}stad [H{\aa}s14]. This optimality of our derandomization translates into the optimality (given current circuit lower bounds) of our PRGs for $\mathsf{AC}^0$ and sparse $\mathbb{F}_2$ polynomials

Multiply Constant-Weight Codes and the Reliability of Loop Physically Unclonable Functions

We introduce the class of multiply constant-weight codes to improve the reliability of certain physically unclonable function (PUF) response. We extend classical coding methods to construct multiply constant-weight codes from known $q$-ary and constant-weight codes. Analogues of Johnson bounds are derived and are shown to be asymptotically tight to a constant factor under certain conditions. We also examine the rates of the multiply constant-weight codes and interestingly, demonstrate that these rates are the same as those of constant-weight codes of suitable parameters. Asymptotic analysis of our code constructions is provided

Doctor of Philosophy

dissertationSynthetic biology is a new field in which engineers, biologists, and chemists are working together to transform genetic engineering into an advanced engineering discipline, one in which the design and construction of novel genetic circuits are made possible through the application of engineering principles. This dissertation explores two engineering strategies to address the challenges of working with genetic technology, namely the development of standards for describing genetic components and circuits at separate yet connected levels of detail and the use of Genetic Design Automation (GDA) software tools to simplify and speed up the process of optimally designing genetic circuits. Its contributions to the field of synthetic biology include (1) a proposal for the next version of the Synthetic Biology Open Language (SBOL), an existing standard for specifying and exchanging genetic designs electronically, and (2) a GDA work ow that enables users of the software tool iBioSim to create an abstract functional specication, automatically select genetic components that satisfy the specication from a design library, and compose the selected components into a standardized genetic circuit design for subsequent analysis and physical construction. Ultimately, this dissertation demonstrates how existing techniques and concepts from electrical and computer engineering can be adapted to overcome the challenges of genetic design and is an example of what is possible when working with publicly available standards for genetic design