An Approach to the Formation of Test Sequences Based on the Graph Model of the Cache Memory Hierarchy

2020 ◽  
Vol 25 (6) ◽  
pp. 548-557
Author(s):  
A.V. Garashchenko ◽  
◽  
L.G. Gagarina ◽  
◽  

The verification of the cache memory hierarchy in modern SoC due to the large state space requires a huge number of complex tests. This becomes the main problem for functional verification. To cover the entire state space, a graph model of the cache memory hierarchy as well as the methods of generating the formation of the test sequences based on this model have been proposed. The graph model vertices are a set of states (tags, values, etc.) of each hierarchy level, and the edges are a set of transitions between states (instructions for reading, records). The graph model, describing all states of the cache-memory hierarchy states, has been developed. Each edge in the graph is a separate check sequence. In case of the non-deterministic situations, such as the choice of a channel (port) for multichannel cache memory, it will not be possible to resolve them at the level of the graph model, since the choice of the channel depends on many factors not considered within the model framework. It has been proposed to create a separate instance of a subgraph for each channel. The described approach has revealed, in verification of the multiport cache-memory hierarchy of the developed core with the new vector architecture VLIW DSP, a few architectural and functional errors. This approach can be used to test other processor cores and their blocks

2015 ◽  
Vol 47 (01) ◽  
pp. 37-56
Author(s):  
Louigi Addario-Berry ◽  
Tao Lei

‘Small worlds’ are large systems in which any given node has only a few connections to other points, but possessing the property that all pairs of points are connected by a short path, typically logarithmic in the number of nodes. The use of random walks for sampling a uniform element from a large state space is by now a classical technique; to prove that such a technique works for a given network, a bound on the mixing time is required. However, little detailed information is known about the behaviour of random walks on small-world networks, though many predictions can be found in the physics literature. The principal contribution of this paper is to show that for a famous small-world random graph model known as the Newman-Watts small-world model, the mixing time is of order log2 n. This confirms a prediction of Richard Durrett [5, page 22], who proved a lower bound of order log2 n and an upper bound of order log3 n.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 14947-14958
Author(s):  
Zhao Lv ◽  
Shuming Chen ◽  
Tingrong Zhang ◽  
Yaohua Wang

2011 ◽  
Vol 52 (4) ◽  
pp. 372-390
Author(s):  
DUNG TIEN NGUYEN ◽  
XUERONG MAO ◽  
G. YIN ◽  
CHENGGUI YUAN

AbstractThis paper considers singular systems that involve both continuous dynamics and discrete events with the coefficients being modulated by a continuous-time Markov chain. The underlying systems have two distinct characteristics. First, the systems are singular, that is, characterized by a singular coefficient matrix. Second, the Markov chain of the modulating force has a large state space. We focus on stability of such hybrid singular systems. To carry out the analysis, we use a two-time-scale formulation, which is based on the rationale that, in a large-scale system, not all components or subsystems change at the same speed. To highlight the different rates of variation, we introduce a small parameter ε>0. Under suitable conditions, the system has a limit. We then use a perturbed Lyapunov function argument to show that if the limit system is stable then so is the original system in a suitable sense for ε small enough. This result presents a perspective on reduction of complexity from a stability point of view.


2016 ◽  
Vol 73 (8) ◽  
pp. 1261-1270 ◽  
Author(s):  
Timothy J. Miller ◽  
Jonathan A. Hare ◽  
Larry A. Alade

The state-space model framework provides a natural, probabilistic approach to stock assessment by modeling the stochastic nature of population survival and recruitment separately from sampling uncertainty inherent in observations on the population. We propose a state-space assessment model that is expanded to simultaneously treat environmental covariates as stochastic processes and estimate their effects on recruitment. We apply the model to southern New England yellowtail flounder (Limanda ferruginea) using data from the most recent benchmark assessment to evaluate evidence for effects of the mid-Atlantic cold pool and spawning stock biomass on recruitment. Based on Akaike’s information criterion, both the cold pool and spawning stock biomass were important predictors of recruitment and led to annual variation in estimated biomass reference points and associated yield. We also demonstrate the effect of the stochasticity of the mid-Atlantic cold pool on short-term forecasts of the stock size, biomass reference point, and stock status.


2012 ◽  
Vol 52 ◽  
pp. 372
Author(s):  
Dung Tien Nguyen ◽  
Xuerong Mao ◽  
George Yin ◽  
Chenggui Yuan

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