IET Computers and Digital Techniques最新文献

This study aims for a new 11T static random access memory (SRAM) cell that uses power gating transistors and transmission gate for low leakage and reliable write operation. The proposed cell has a separate read and write path which successfully improves read and write abilities. Furthermore, it solves the row half select disturbance and utilises a row-based virtual ground signal to eliminate unnecessary bit-line discharge in the un-selected row, thus decreasing energy consumption. The cell also achieves low power due to the stack effect. To show the effectiveness of the cell, its design metrics are compared with other published SRAM cells, namely, conventional 6T, 10T, 9T, and power-gated 9T (PG9T). In standby mode, from 6.71 to 7.37% leakage power reduction is observed for this cell at an operating voltage of 1.2 V and 29.21 to 58.68% & 32.74 to 71.11% improvement for write & read power over other cells. The proposed cell exhibits higher write and reads static noise margins with an improvement of 13.54 and 63.28%, respectively, compared to conventional 6T SRAM cell. The cell provides write delay improvement from 29.77 to 49.40% and read delay improvement from 7 to 12% compared to 9T, 10T, and PG9T, respectively.

Microfluidics is an upcoming field of science that is going to be used widely in many safety-critical applications including healthcare, medical research and defence. Hence, technologies for fault testing and fault diagnosis of these chips are of extreme importance. In this study, the authors propose a scalable pseudo-exhaustive testing and diagnosis methodology for flow-based microfluidic biochips. The proposed approach employs a divide-and-conquer based technique wherein, large architectures are split into smaller sub-architectures and each of these are tested and diagnosed independently.

The incessant growth of devices such as mobile phones, digital cameras, and other portable electronic gadgets has led to a higher amount of research being dedicated to the low power digital and analogue circuits. In this study, a low power-delay-product (PDP) dynamic complementary metal oxide semiconductor (CMOS) circuit design using small swing domino logic with twist-connected transistors is proposed. An improvement in PDP can be achieved by using a node-discharger circuit in the conventional design. The conventional benchmark and modified circuits are implemented in 90 nm CMOS technology with different power supplies, i.e. 1.2, 1, and 0.9 V. Furthermore, a decrease in voltage level for logic ‘1’ and an increase in voltage level for logic ‘0’ is achieved while maintaining the logic threshold accordingly at half of the supply voltage. So, the output voltage swing is reduced and the unnecessary nodes of the pull down network get discharged in pre-charge phase, eventually leading to an improvement when compared with conventional design in overall PDP by 43.21 and 46.83% for two inverted two-input and three-input AND gate dynamic benchmarks, respectively, for a power supply of 1 V.

Spin-transfer torque random access memory (STT-RAM) has emerged as an eminent choice for the larger on-chip caches due to high density, low static power consumption and scalability. However, this technology suffers from long latency and high energy consumption during a write operation. Hybrid caches alleviate these problems by incorporating a write-friendly memory technology such as static random access memory along with STT-RAM technology. The proper allocation of data blocks has a significant effect on both performance and energy consumption in the hybrid cache. In this study, the allocation and migration problem of data blocks in the hybrid cache is examined and then modelled using integer linear programming (ILP) formulations. The authors propose an ILP model with three different objective functions which include minimising access latency, minimising energy and minimising energy-delay product in the hybrid cache. Evaluations confirm that the proposed ILP model obtains better results in terms of energy consumption and performance compared to the existing hybrid cache architecture.

As technology scales down, circuits are more prone to incur in faults and fault detection is necessary to ensure the system reliability. However, fault-detection circuits are also vulnerable to stuck-at faults due to, for example, manufacturing defects or ageing; a fault can cause an incorrect output in the fault-detection scheme; so concurrent fault detection is, therefore, needed. Cyclic redundancy checks (CRCs) are widely used to detect errors in many applications, for example, they are used in communication to detect errors on transmitted frames. In this study, an efficient method to implement concurrent fault detection for parallel CRC computation is proposed. The scheme relies on using a serial CRC computation circuit that is used to periodically check the results obtained from the main module to detect the faults. This introduces a lower circuit overhead than existing schemes. All CRC encoders and decoders that implement the CRC computation in parallel can employ the proposed scheme to detect faults.

A major issue faced by data scientists today is how to scale up their processing infrastructure to meet the challenge of big data and high-performance computing (HPC) workloads. With today's HPC domain, it is required to connect multiple graphics processing units (GPUs) to accomplish large-scale parallel computing along with CPUs. Data movement between the processor and on-chip or off-chip memory creates a major bottleneck in overall system performance. The CPU/GPU processes all the data on a computer's memory and hence the speed of the data movement to/from memory and the size of the memory affect computer speed. During memory access by any processing element, the memory management unit (MMU) controls the data flow of the computer's main memory and impacts the system performance and power. Change in dynamic random access memory (DRAM) architecture, integration of memory-centric hardware accelerator in the heterogeneous system and Processing-in-Memory (PIM) are the techniques adopted from all the available shared resource management techniques to maximise the system throughput. This survey study presents an analysis of various DRAM designs and their performances. The authors also focus on the architecture, functionality, and performance of different hardware accelerators and PIM systems to reduce memory access time. Some insights and potential directions toward enhancements to existing techniques are also discussed. The requirement of fast, reconfigurable, self-adaptive memory management schemes in the high-speed processing scenario motivates us to track the trend. An effective MMU handles memory protection, cache control and bus arbitration associated with the processors.

In this study, high-throughput and flexible hardware implementations of the CLEFIA lightweight block cipher are presented. A unified processing element is designed and shared for implementing of generalised Feistel network that computes round keys and encryption process in the two separate times. The most complex blocks in the CLEFIA algorithm are substitution boxes ( and ). The S-box is implemented based on area-optimised combinational logic circuits. In the proposed S-box structure, the number of logic gates and critical path delay are reduced by using the simplification of computation terms. The S-box consists of three steps: a field inversion over and two affine transformations over . The inversion operation is implemented over the composite field instead of inversion over which is an important factor for the reduction of area consumption. In addition, we proposed a flexible structure that can perform various configurations of CLEFIA to support variable key sizes: 128, 192 and 256 bit. Implementation results of the proposed architectures in 180 nm complementary metal–oxide–semiconductor technology for different key sizes are achieved. The results show improvements in terms of execution time, throughput and throughput/area compared with other related works.