A hybrid method for signal probability and reliability estimation with combinational circuits

Zhan, Suoyue; Chen, Chunhong

doi:10.1016/j.vlsi.2022.07.006

Cited by 4 publications

(9 citation statements)

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“…Additionally, it demonstrated superior computational efficiency, with an average processing time of 0.9483, while the other methods required more time, with averages of 4.23 and 4.207, respectively. Notably, the reliability estimation results from the proposed method slightly outperformed those of [12] and [25]. One of the crucial aspects of the reliability calculation method is its efficiency in handling large circuits, aiming to achieve both accurate results and reasonable computation time while minimizing the computational workload.…”

Section: Simulation Results With Discussionmentioning

confidence: 98%

“…Figure 7 shows the maximum size of the output probability matrix for the ISCAS'85 benchmark circuits. For example, in circuit C3540, the size of the output probability matrix, without applying the gate output probability calculation algorithm and considering all states, is equal to 2 25 . By considering the algorithm, the size of this matrix is reduced to 4096 (2 12 ).…”

Section: Simulation Results With Discussionmentioning

confidence: 99%

“…By considering the algorithm, the size of this matrix is reduced to 4096 (2 12 ). In other words, the output probability matrix with size 2 25 is repeated as 8192(2 25−15) ). By avoiding the recalculation of these repeated values, the volume of calculations is significantly reduced.…”

Section: Simulation Results With Discussionmentioning

confidence: 99%

“…In this equation, 𝑃 𝑥 (𝑃 𝑥 = 1 − 𝑄 𝑥 ) represents the probability of a circuit node being in the state '1' [18]. This probability is computed within an error-free circuit using the bit stream method, which bears resemblance to the approach described in references [22] and [25].…”

Section: A the Fault Propagation Matrixmentioning

confidence: 99%

“…Recent approaches introduced correlation coefficients to evaluate signal correlations. However, they either rely on rough estimations or exhibit relatively large errors [24], [25], [26].…”

Section: Introductionmentioning

confidence: 99%

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An Effective Fanout-Based Method for Improving Error Propagation Probability Estimation in Combinational Circuits

Esmaieli,

Peiravi,

Sedaghat

2024

IEEE Access

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The downsizing of nanoscale circuits imposes new challenges for circuit reliability, including hard defects, soft errors and unsaturated voltage/current. Many studies on the reliability of digital circuits have focused on achieving accurate reliability estimation and more efficiency for larger circuits. To achieve accurate reliability estimation, it is necessary to address the issue of error propagation and consider correlated signals from reconverging paths in reliability calculations. In this paper, an error propagation probability model for each gate, which takes into account the probability of an unreliable logic gate's input signal and relates it to the probability of the output signal is proposed. Additionally, we introduce an efficient approach that utilizes a new fanout matrix to tackle the reconvergent fanouts problem. Furthermore, to ensure an accurate estimation of combinational logic circuit reliability, the probabilities obtained for each fanout should be included in the calculations by defining a fanout probability matrix. To address this issue, a new method is proposed at each calculation stage, aiming to minimize computational complexity making it suitable for large circuits with a significant number of fanouts. We conducted various simulations to demonstrate the accuracy and scalability of the proposed method on the ISCAS 85 benchmark circuit and EPFL Benchmark. The results show less than 1% average relative error in reliability estimation and outperform state-of-the-art methods in reliability estimation and algorithm runtime.

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Section: Simulation Results With Discussionmentioning

confidence: 98%

Section: Simulation Results With Discussionmentioning

confidence: 99%

Section: Simulation Results With Discussionmentioning

confidence: 99%

Section: A the Fault Propagation Matrixmentioning

confidence: 99%

“…Recent approaches introduced correlation coefficients to evaluate signal correlations. However, they either rely on rough estimations or exhibit relatively large errors [24], [25], [26].…”

Section: Introductionmentioning

confidence: 99%

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