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Shadow is a lightweight AND‐RX block cipher adapted for resource‐constrained devices. In this paper, software and hardware optimizations are proposed respectively for Shadow to enhance its implementation performance. For software optimization, this paper first proposes a data pre‐processing scheme based on the structural characteristics of the round function. It further improves the optimization effect of the barrel shifter instruction while simplifying the implementation process of the round function. Note that the optimization strategy is also applicable to other AND‐RX ciphers. Secondly, this paper proposes a new NX operation implementation scheme that can effectively reduce its instruction cycles. In round‐based architecture, experimental results show that our scheme effectively reduces code size by 24.7%, Flash consumption by 12.6%, and total instruction cycles by 25.1%. Meanwhile, in the fully unrolled architecture, our scheme reduces code size by 30.8%, Flash consumption by 29.8%, and total instruction cycles by 28.1%. For hardware optimization, this paper proposes a low‐resource implementation scheme by constructing a generic formula for NX operation. In ASIC implementation, our scheme reduces hardware resources by 72.3%. In FPGA implementation, the number of LUTs and Slices is reduced by 30% and 28.6%, respectively. Overall, the proposed optimization scheme for Shadow has better performance in hardware and software implementation.
Shadow is a lightweight AND‐RX block cipher adapted for resource‐constrained devices. In this paper, software and hardware optimizations are proposed respectively for Shadow to enhance its implementation performance. For software optimization, this paper first proposes a data pre‐processing scheme based on the structural characteristics of the round function. It further improves the optimization effect of the barrel shifter instruction while simplifying the implementation process of the round function. Note that the optimization strategy is also applicable to other AND‐RX ciphers. Secondly, this paper proposes a new NX operation implementation scheme that can effectively reduce its instruction cycles. In round‐based architecture, experimental results show that our scheme effectively reduces code size by 24.7%, Flash consumption by 12.6%, and total instruction cycles by 25.1%. Meanwhile, in the fully unrolled architecture, our scheme reduces code size by 30.8%, Flash consumption by 29.8%, and total instruction cycles by 28.1%. For hardware optimization, this paper proposes a low‐resource implementation scheme by constructing a generic formula for NX operation. In ASIC implementation, our scheme reduces hardware resources by 72.3%. In FPGA implementation, the number of LUTs and Slices is reduced by 30% and 28.6%, respectively. Overall, the proposed optimization scheme for Shadow has better performance in hardware and software implementation.
In Very-Large-Scale-Integration (VLSI) designs, thorough testing is indispensable for identifying the structural defects of the chip. Timely detection and correcting serious defects are pivotal in preventing faulty chips from reaching customers and avoiding failures. In scan designs, the toggling activity is a critical factor due to the defects between lower cells and metal layers, exacerbated by diverse Process, Voltage, and Temperature (PVT) conditions. These defects significantly impact design testability, quality, and reliability, necessitating meticulous testing to ensure that chips meet the desired specifications. Effectively managing power consumption in the current VLSI landscape is crucial amid the ongoing energy crisis. Balancing the need for Low-Power (LP) with the complexity of integrating transistors onto a single silicon substrate poses significant challenges. As chip densities increase, power dissipation during testing surges, adversely affecting durability, performance, cost, and reliability. Engineers are racing to optimize test power usage, employing advanced Design for Test (DFT) techniques to incorporate efficient power management into Silicon-on-Chip (SoC) designs. Linear Feedback Shift Registers (LFSRs) are phenomenal in addressing DFT parameters like power, and performance, and for better pseudo-random pattern generation. Hence, this paper proposes a groundbreaking approach to power reduction techniques deploying the LFSR architecture, and thus challenging conventional scan-based testing methods. The proposed LFSR architecture is meticulously designed and rigorously tested using Cadence DFT Modus solution on ISCAS’89 benchmarking circuits. Coverage was unequivocally evaluated for Quality of Results (QoR) metrics, such as fault coverage, memory usage, pattern counts, switching activity, fault testing, and runtime. The specific evaluation clearly proved the superiority of the LFSR-based approach over the scan-based architecture. Adopting the novel LFSR architecture resulted in a ~5.6X reduction in toggling activity accompanied by a substantial ~10K pattern reduction and a runtime of nearly ~1.5 hours. Notably, the test power was reduced to 50% showcasing superior efficiency. This approach emerges as the ideal solution for industrial designs providing the best QoR for power, performance, and area. This innovative methodology marks a significant leap toward an energy-efficient and cost-effective VLSI circuit especially for stacked 2.5-3D ICs and chiplets poised to revolutionize chip manufacturing.
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