IET Computers and Digital Techniques最新文献

A configurable self-calibrated power efficient five-bit error correction code is proposed to correct both single bit random and burst errors up to five bits; providing 100% error correction probability with crosstalk avoidance. It can also correct higher-order error up to 9 bits with an error correction probability tolerance of 73% for on-chip interconnection links. Single error correction and double error detection with extended Hamming code (22,16) is utilised along with standard triplication error correction methods in the proposed code. Self-calibration algorithm and data stream rerouting block are integrated into the error correction code to achieve power efficiency. Reliability, link power consumption, and link swing voltage are estimated using an analytical model used in a network-on-chip. Area, power, and delay of the codec are obtained using Synopsys tools utilising UMC 90 nm technology. The proposed method provides 32–73% power saving and 22.3–60.6% delay reduction with negligible area overhead compared with the state-of-the-art works. Estimated results prove that it provides a 40.5–50% reduction in link swing voltage and link power consumption compared with the state-of-the-art works. The proposed code is more appropriate for on-chip interconnect links where it provides high reliability and low swing voltage with high error correction capability compared with existing codes.

Hardware Trojan detection techniques have been studied extensively. However, to develop reliable and effective defenses, it is important to figure out how hardware Trojans are implemented in practical scenarios. The authors attempt to make a review of the hardware Trojan design and implementations in the last decade and also provide an outlook. Unlike all previous surveys that discuss Trojans from the defender's perspective, for the first time, the authors study the Trojans from the attacker's perspective, focusing on the attacker's methods, capabilities, and challenges when the attacker designs and implements a hardware Trojan. First, the authors present adversarial models in terms of the adversary's methods, adversary's capabilities, and adversary's challenges in seven practical hardware Trojan implementation scenarios: in-house design team attacks, third-party intellectual property vendor attacks, computer-aided design tools attacks, fabrication stage attacks, testing stage attacks, distribution stage attacks, and field-programmable gate array Trojan attacks. Second, the authors analyse the hardware Trojan implementation methods under each adversarial model in terms of seven aspects/metrics: hardware Trojan attack scenarios, the attacker's motivation, feasibility, detectability (anti-detection capability), protection and prevention suggestions for the designer, overhead analysis, and case studies of Trojan implementations. Finally, future directions on hardware Trojan attacks and defenses are also discussed.

With the development of network-on-chip (NoC) theory, lots of mapping algorithm have been proposed to solve the application mapping problem which is an NP-hard (non-polynomial hard) problem. Most algorithms are based on a heuristic algorithm. They are trapped by iterations limited, not by the distance between iterations, because of the isomorphism of mapping sequence. In this study, the authors define and analyse the isomorphism with the genetic algorithm (GA) which is a heuristic algorithm. Then, they proposed an approach called density direction transform algorithm to eliminate the isomorphism of mapping sequence and accelerate the convergence of population. To verify this approach, they developed a density-direction-based genetic mapping algorithm (DDGMAP) and make a comparison with genetic mapping algorithm (GMA). The experiment demonstrates that compared to the random algorithm, their algorithm (DDGMAP) can achieve on an average 23.48% delay reduction and 7.15% power reduction. And DDGMAP gets better performance than GA in searching the optimal solution.

Quantum computers that are based on technologies like superconducting and quantum dots impose a physical constraint that requires interacting qubits to be adjacent. The initial placement of qubits and the swap gate insertion techniques affect the circuit cost. The authors proposed a global qubit ordering technique that considers fewer permutations for the number of interactions a qubit does with other qubits of its circuit. They also performed the local re-ordering of qubits by attempting to reduce the cost as much as possible; the cost is estimated by defining a window with weights assigned in such a way that nearby gates to the current gate in question are given higher weightage. Experiments have been conducted on NCV benchmarks, and results have been compared with those of recent state-of-the-art techniques. When compared with the existing works, the proposed method shows improvements of up to 53.3% for smaller benchmarks and up to 51.61% for larger benchmarks.

In this study, the authors present a novel speech enhancement method by exploring the benefits of non-local means (NLM) estimation and optimised empirical mode decomposition (OEMD) adopting cubic-spline interpolation. The optimal parameters responsible for improving the performance are estimated using the path-finder algorithm. At first, the noisy speech signal is decomposed into many scaled signals called intrinsic-mode functions (IMFs) through the use of a temporary decomposition method is called sifting process in OEMD approach. The obtained IMFs are processed by NLM estimation technique in terms of non-local similarities present in each IMF, to reduce the ill-effects caused by interfering noise. The proposed NLM-based method is effective to eliminate the noise of less-frequency. Each IMF contains essential information about the signals, on some scale or frequency band. Field programmable gate array architecture is implemented on a Xilinx ISE 14.5 and the result of the proposed method offers good performance with a high signal-to-noise ratio (SNR) and low mean-square error compared to other approaches. The performance evolution is carried out for different speech signals taken from the TIMIT database and noises taken from the NOISEX-92 database in different SNR stages of 0, 5 and 10 dB, respectively.

The coupling capacitance and inductance of 2D and 3D integrated circuit (IC) interconnects in deep sub-micron technology has been increased due to reduced coupling distance in such a way that their magnitudes become comparable to the area and fringing capacitance of an interconnect. This leads to an increasing risk of failure due to unintentional noise and a need for accurate noise assessment. Incorrect noise estimation could either result in defects in circuit design if the design resources are understated or it will end up with a waste of overestimation resources. In this study, a crosstalk noise model for coupled RLC on-chip interconnects has been demonstrated. Subsequently, a novel time-efficient method is proposed to estimate and optimise the crosstalk noise precisely. The proposed method calculates coupling noise as well as optimises crosstalk noise, which has been validated using SPICE. Besides the estimation of crosstalk noise for 2D interconnect, this study also estimates the crosstalk noise for through-silicon-via (TSV), which is used to connect different dies vertically in a 3D IC. Under high-frequency operation, effects of signal rise time, TSV structure (height of the TSV), substrate resistivity and the guarding TSV termination on crosstalk noise have also been studied in this work.