Secure, performance-oriented data management for nanoCMOS electronics

The EPSRC pilot project Meeting the Design Challenges of nanoCMOS Electronics (nanoCMOS) is focused upon delivering a production level e-Infrastructure to meet the challenges facing the semiconductor industry in dealing with the next generation of ‘atomic-scale’ transistor devices. This scale means that previous assumptions on the uniformity of transistor devices in electronics circuit and systems design are no longer valid, and the industry as a whole must deal with variability throughout the design process. Infrastructures to tackle this problem must provide seamless access to very large HPC resources for computationally expensive simulation of statistic ensembles of microscopically varying physical devices, and manage the many hundreds of thousands of files and meta-data associated with these simulations. A key challenge in undertaking this is in protecting the intellectual property associated with the data, simulations and design process as a whole. In this paper we present the nanoCMOS infrastructure and outline an evaluation undertaken on the Storage Resource Broker (SRB) and the Andrew File System (AFS) considering in particular the extent that they meet the performance and security requirements of the nanoCMOS domain. We also describe how metadata management is supported and linked to simulations and results in a scalable and secure manner

Compact Structural Test Generation for Analog Macros

A structural, fault-model based methodology for the generation of compact high-quality test sets for analog macros is presented. Results are shown for an IV-converter macro design. Parameters of so-called test configurations are optimized for detection of faults in a fault-list and an optimal selection algorithm results in determining the best test set. The distribution of the results along the parameter-axes of the test configurations is investigated to identify a collapsed high-quality test se

High Quality Compact Delay Test Generation

Delay testing is used to detect timing defects and ensure that a circuit meets its timing specifications. The growing need for delay testing is a result of the advances in deep submicron (DSM) semiconductor technology and the increase in clock frequency. Small delay defects that previously were benign now produce delay faults, due to reduced timing margins. This research focuses on the development of new test methods for small delay defects, within the limits of affordable test generation cost and pattern count. First, a new dynamic compaction algorithm has been proposed to generate compacted test sets for K longest paths per gate (KLPG) in combinational circuits or scan-based sequential circuits. This algorithm uses a greedy approach to compact paths with non-conflicting necessary assignments together during test generation. Second, to make this dynamic compaction approach practical for industrial use, a recursive learning algorithm has been implemented to identify more necessary assignments for each path, so that the path-to-test-pattern matching using necessary assignments is more accurate. Third, a realistic low cost fault coverage metric targeting both global and local delay faults has been developed. The metric suggests the test strategy of generating a different number of longest paths for each line in the circuit while maintaining high fault coverage. The number of paths and type of test depends on the timing slack of the paths under this metric. Experimental results for ISCAS89 benchmark circuits and three industry circuits show that the pattern count of KLPG can be significantly reduced using the proposed methods. The pattern count is comparable to that of transition fault test, while achieving higher test quality. Finally, the proposed ATPG methodology has been applied to an industrial quad-core microprocessor. FMAX testing has been done on many devices and silicon data has shown the benefit of KLPG test

Automated Netlist Generation for 3D Electrothermal and Electromagnetic Field Problems

We present a method for the automatic generation of netlists describing general three-dimensional electrothermal and electromagnetic field problems. Using a pair of structured orthogonal grids as spatial discretisation, a one-to-one correspondence between grid objects and circuit elements is obtained by employing the finite integration technique. The resulting circuit can then be solved with any standard available circuit simulator, alleviating the need for the implementation of a custom time integrator. Additionally, the approach straightforwardly allows for field-circuit coupling simulations by appropriately stamping the circuit description of lumped devices. As the computational domain in wave propagation problems must be finite, stamps representing absorbing boundary conditions are developed as well. Representative numerical examples are used to validate the approach. The results obtained by circuit simulation on the generated netlists are compared with appropriate reference solutions.Comment: This is a pre-print of an article published in the Journal of Computational Electronics. The final authenticated version is available online at: https://dx.doi.org/10.1007/s10825-019-01368-6. All numerical results can be reproduced by the Matlab code openly available at https://github.com/tc88/ANTHE

Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable circuit overhead. Here we describe a hardware architecture that can feature a large number of memristor synapses to learn real-world patterns. We present a versatile CMOS neuron that combines integrate-and-fire behavior, drives passive memristors and implements competitive learning in a compact circuit module, and enables in-situ plasticity in the memristor synapses. We demonstrate handwritten-digits recognition using the proposed architecture using transistor-level circuit simulations. As the described neuromorphic architecture is homogeneous, it realizes a fundamental building block for large-scale energy-efficient brain-inspired silicon chips that could lead to next-generation cognitive computing.Comment: This is a preprint of an article accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol 5, no. 2, June 201

Neutral conductor current in three-phase networks with compact fluorescent lamps

In this paper, expressions of the neutral conductor current in three-phase networks with compact fluorescent lamps (CFLs) are obtained from a CFL “black-box” model proposed in the literature. These expressions allow studying and performing a sensitivity analysis of the impact of CFLs on neutral current. The influence of CFL model parameters, as well as supply voltage unbalance, number of CFLs per phase and different types of CFLs per phase, on the neutral current is also investigated. The obtained results are validated with measurements and PSCAD/EMTDC simulationsPeer ReviewedPreprin