Probabilistic Transfer Matrix Model Research Articles

Accurate reliability analysis methods for approximate computing circuits

In recent years, Approximate Computing Circuits (ACCs) have been widely used in applications with intrinsic tolerance to errors. With the increased availability of approximate computing circuit approaches, reliability analysis methods for assessing their fault vulnerability have become highly necessary. In this study, two accurate reliability evaluation methods for approximate computing circuits are proposed. The reliability of approximate computing circuits is calculated on the basis of the iterative Probabilistic Transfer Matrix (PTM) model. During the calculation, the correlation coefficients are derived and combined to deal with the correlation problem caused by fanout reconvergence. The accuracy and scalability of the two methods are verified using three sets of approximate computing circuit instances and more circuits in EvoApprox8b, which is an approximate computing circuit open source library. Experimental results show that relative to the Monte Carlo simulation, the two methods achieve average error rates of 0.46% and 1.29% and time overheads of 0.002% and 0.1%. Different from the existing approaches to reliability estimation for approximate computing circuits based on the original PTM model, the proposed methods reduce the space overheads by nearly 50% and achieve time overheads of 1.78% and 2.19%.

A Novel Trust Evaluation Method for Logic Circuits in IoT Applications Based on the E-PTM Model

The increase in the reliability requirements of integrated circuits applied in diverse smart sensing devices and the increase in the cost of test generation and fault simulation have expanded the need for new approaches to estimate signal reliability in logic circuits, which will help trust management of Internet of Things smart systems. This paper presents a novel method for reliability analysis in logic circuits with unreliable devices for application in trust-driven design. Based on the extended probabilistic transfer matrix model with binary-decimal coding allocation, by using the technologies of state-vector expansion and matrix reconstruction, the proposed method evaluates the quality of a reliability improvement for trust-driven design applications, while maintaining high computational accuracy, in early stages of circuit design. This efficiency is possible, because the proposed method is always computed in units of basic gates and the reliability can be output by an observable matrix with hybrid coding. Simulation results on benchmark circuits show that the proposed method is an accurate and fast method with less complexity and will contribute to the dynamic analysis of circuit reliability in circuit design.

Blockchain Architecture Reliability-Based Measurement for Circuit Unit Importance

Currently, few works focus on the reliability of the blockchain architecture at the circuit level, which makes its security and privacy vulnerable to hardware errors. To mitigate the hazard, through an iterative probabilistic transfer matrix model coded by a binary-decimal mechanism, a reliability-based evaluation method for the importance of circuit units is proposed in this paper. First, the method calculates the output reliabilities in any leads by the iterative probabilistic transfer matrix model and obtains the reliability gradient for the circuit units based on the gradient and barrel theory. Second, it sorts the importance of the circuit units based on their obtained reliability gradients. Third, combining the sensitized path coverage rate and the sequence comparison, the method constructs an importance-based sorting algorithm for the circuit units with the same reliability gradients. Finally, it reinforces the importance circuit units based on the sorting results to improve the security and privacy for the blockchain architecture at the hardware level. Theoretical analysis and experimental results indicate that the proposed method can be applied to measure the importance of circuit units at several abstract levels, with high precision and small time-space complexity, and systems can thus achieve a great reliability improvement at a small cost.

Circuit reliability estimation based on an iterative PTM model with hybrid coding

Using the probabilistic transfer matrix model as the major technology, this paper firstly separated the presentation and quantification of signal relations, and blocked the concurrent signals in fan-out by hybrid coding; secondly a method to construct the output reliability matrixes and output probability distributions of basic circuit components was proposed based on a virtual method; and then a method to achieve the reliability iterative propagation between the pre-stage and post-stage circuit was designed using a weak equivalence principle. The theoretical analysis and experiment results show that the proposed method can be applied to the reliability evaluation for several-abstract-level circuits that have high calculation precision and linear complexity in time and space.

Accurate reliability analysis method for quantum-dot cellular automata circuits

Probabilistic transfer matrix (PTM) is a widely used model in the reliability research of circuits. However, PTM model cannot reflect the impact of input signals on reliability, so it does not completely conform to the mechanism of the novel field-coupled nanoelectronic device which is called quantum-dot cellular automata (QCA). It is difficult to get accurate results when PTM model is used to analyze the reliability of QCA circuits. To solve this problem, we present the fault tree models of QCA fundamental devices according to different input signals. After that, the binary decision diagram (BDD) is used to quantitatively investigate the reliability of two QCA XOR gates depending on the presented models. By employing the fault tree models, the impact of input signals on reliability can be identified clearly and the crucial components of a circuit can be found out precisely based on the importance values (IVs) of components. So this method is contributive to the construction of reliable QCA circuits.

Accurate reliability evaluation using quantum‐dot cellular automata probabilistic transfer matrix

The probabilistic transfer matrix (PTM) plays an important role in analysing the transient faults and the reliability of digital logic circuits. Proposed a modified PTM (QPTM) for quantum-dot cellular automata (QCA). It has two features different from the previous PTM model: (i) finding more accurate matrices for the wires; and (ii) dividing the QCA circuits more reasonably. Simultaneously, the wire's correct probability is curved by a Gaussian function to enable it to emerge successfully. By using this QPTM, the detailed and extensive simulation results gained reveal that the reliabilities obtained from the PTM analysis of the same circuit could differ at 9%. As for the reliabilities achieved from the PTM and the QPTM, the difference rises to 30%. The simulations obtained have proved that the PTM has weaknesses when presenting the effects of the wire's length and division on the circuit reliabilities.