Browsing by Subject "Verification"
Results Per Page
Sort Options
Item Open Access A Differentially Private Bayesian Approach to Replication Analysis(2022) Yang, ChengxinReplication analysis is widely used in many fields of study. Once a research is published, other researchers will conduct analysis to assess the reliability of the published research. However, what if the data are confidential? In particular, if the data sets used for the studies are confidential, we cannot release the results of replication analyses to any entity without the permission to access the data sets, otherwise it may result in privacy leakage especially when the published study and replication studies are using similar or common data sets. In this paper, we present two methods for replication analysis. We illustrate the properties of our methods by a combination of theoretical analysis and simulation.
Item Open Access Differentially Private Verification ofPredictions from Synthetic Data(2017) Yu, HaoyangWhen data are confidential, one approach for releasing public available files is to make synthetic data, i.e, data simulated from statistical models estimated on the confidential data. Given access only to synthetic data, users have no way to tell if the synthetic data can preserve the adequacy of their analysis. Thus, I present methods that can help users to make such assessments automatically while controlling the information disclosure risks in the confidential data. There are three verification methods presented in this thesis: differentially private prediction tolerance intervals, differentially private prediction histogram, and differentially private Kolmogorov-Smirnov test. I use simulation to illustrate these prediction verification methods.
Item Open Access Fractal Consistency: Architecting the Memory System to Facilitate Verification(IEEE COMPUTER ARCHITECTURE LETTERS, 2010) Zhang, M; Lebeck, A; Sorin, DItem Open Access Scalably Verifiable Cache Coherence(2013) Zhang, MengThe correctness of a cache coherence protocol is crucial to the system since a subtle bug in the protocol may lead to disastrous consequences. However, the verification of a cache coherence protocol is never an easy task due to the complexity of the protocol. Moreover, as more and more cores are compressed into a single chip, there is an urge for the cache coherence protocol to have higher performance, lower power consumption, and less storage overhead. People perform various optimizations to meet these goals, which unfortunately, further exacerbate the verification problem. The current situation is that there are no efficient and universal methods for verifying a realistic cache coherence protocol for a many-core system.
We, as architects, believe that we can alleviate the verification problem by changing the traditional design paradigm. We suggest taking verifiability as a first-class design constraint, just as we do with other traditional metrics, such as performance, power consumption, and area overhead. To do this, we need to incorporate verification effort in the early design stage of a cache coherence protocol and make wise design decisions regarding the verifiability. Such a protocol will be amenable to verification and easier to be verified in a later stage. Specifically, we propose two methods in this thesis for designing scalably verifiable cache coherence protocols.
The first method is Fractal Coherence, targeting verifiable hierarchical protocols. Fractal Coherence leverages the fractal idea to design a cache coherence protocol. The self-similarity of the fractal enables the inductive verification of the protocol. Such a verification process is independent of the number of nodes and thus is scalable. We also design example protocols to show that Fractal Coherence protocols can attain comparable performance compared to a traditional snooping or directory protocol.
As a system scales hierarchically, Fractal Coherence can perfectly solve the verification problem of the implemented cache coherence protocol. However, Fractal Coherence cannot help if the system scales horizontally. Therefore, we propose the second method, PVCoherence, targeting verifiable flat protocols. PVCoherence is based on parametric verification, a widely used method for verifying the coherence of a flat protocol with infinite number of nodes. PVCoherence captures the fundamental requirements and limitations of parametric verification and proposes a set of guidelines for designing cache coherence protocols that are compatible with parametric verification. As long as designers follow these guidelines, their protocols can be easily verified.
We further show that Fractal Coherence and PVCoherence can also facilitate the verification of memory consistency, another extremely challenging problem. One piece of previous work proves that the verification of memory consistency can be decomposed into three steps. The most complex and non-scalable step is the verification of the cache coherence protocol. If we design the protocol following the design methodology of Fractal Coherence or PVCoherence, we can easily verify the cache coherence protocol and overcome the biggest obstacle in the verification of memory consistency.
As system expands and cache coherence protocols get more complex, the verification problem of the protocol becomes more prominent. We believe it is time to reconsider the traditional design flow in which verification is totally separated from the design stage. We show that by incorporating the verifiability in the early design stage and designing protocols to be scalably verifiable in the first place, we can greatly reduce the burden of verification. Meanwhile, we perform various experiments and show that we do not lose benefits in performance as well as in other metrics when we obtain the correctness guarantee.