What is the Path to Fast Fault Simulation?

Motivated by the recent advances in fast fault simulation techniques for large combinational circuits, a panel discussion has been organized for the 1988 International Test Conference. This paper is a collective account of the position statements offered by the panelists

Built-In Self-Test Quality Assessment Using Hardware Fault Emulation in FPGAs

This paper addresses the problem of test quality assessment, namely of BIST solutions, implemented in FPGA and/or in ASIC, through Hardware Fault Emulation (HFE). A novel HFE methodology and tool is proposed, that, using partial reconfiguration, efficiently measures the quality of the BIST solution. The proposed HFE methodology uses Look-Up Tables (LUTs) fault models and is performed using local partial reconfiguration for fault injection on Xilinx(TM) Virtex and/or Spartan FPGA components, with small binary files. For ASIC cores, HFE is used to validate test vector selection to achieve high fault coverage on the physical structure. The methodology is fully automated. Results on ISCAS benchmarks and on an ARM core show that HFE can be orders of magnitude faster than software fault simulation or fully reconfigurable hardware fault emulation

Testability Analysis of Synchronous Sequential Circuits Based On Structural Data

Bounds on test sequence length can be used as a testability measure. We give a procedure to compute the upper bound on test sequence length for an arbitrary sequential circuit. We prove that the bound is exact for a certain class of circuits. Three design rules are specified to yield circuits with lower test sequence bounds

Efficient VLSI fault simulation

AbstractLet C be an acyclic Boolean circuit with n gates and ≤ n inputs. A circuit manufacture error may result in a “Stuck-at” (S-A) fault in a circuit identical to C except a gate v only outputs a fixed Boolean value. The S-A fault simulation problem for C is to determine all possible (S-A) faults which can be detected (i.e., faults circuit and C would give distinct outputs) by a given test pattern input.We consider the case where C is a tree (i.e., has fan-out 1.)We give a practical algorithm for fault simulation which simultaneously determines all detectable S-A faults for every gate in the circuit tree C. Our algorithm required only the evaluation of a circuit FS(C) which has ≤ 7n gates and has depth ≤ 3(d + 1), when d is the depth of C. Thus the sequential time of our algorithm is ≤ 7n, and the parallel time is ≤ 3(d + 1). Furthermore, FS(C) requires only a small constant factor more VLSI area than does the original circuit C.We also extend our results to get efficient methods for fault simulation of oblivious VLSI circuits with feedback lines

RosneT: A block tensor algebra library for out-of-core quantum computing simulation

With the advent of more powerful Quantum Computers, the need for larger Quantum Simulations has boosted. As the amount of resources grows exponentially with size of the target system Tensor Networks emerge as an optimal framework with which we represent Quantum States in tensor factorizations. As the extent of a tensor network increases, so does the size of intermediate tensors requiring HPC tools for their manipulation. Simulations of medium-sized circuits cannot fit on local memory, and solutions for distributed contraction of tensors are scarce. In this work we present RosneT, a library for distributed, out-of-core block tensor algebra. We use the PyCOMPSs programming model to transform tensor operations into a collection of tasks handled by the COMPSs runtime, targeting executions in existing and upcoming Exascale supercomputers. We report results validating our approach showing good scalability in simulations of Quantum circuits of up to 53 qubits.We acknowledge support from project QuantumCAT (ref. 001- P-001644), co-funded by the Generalitat de Catalunya and the European Union Regional Development Fund within the ERDF Operational Program of Catalunya, and European Union’s Horizon 2020 research and innovation programme under grant agreement No 951911 (AI4Media). This work has also been partially supported by the Spanish Government (PID2019-107255GB) and by Generalitat de Catalunya (contract 2014-SGR-1051). This work is co-funded by the European Regional Development Fund under the framework of the ERFD Operative Programme for Catalunya 2014-2020, with 1.527.637,88C. Anna Queralt is a Serra Hunter Fellow.Peer ReviewedPostprint (author's final draft

Real-Time Trace Decoding and Monitoring for Safety and Security in Embedded Systems

Integrated circuits and systems can be found almost everywhere in today’s world. As their use increases, they need to be made safer and more perfor mant to meet current demands in processing power. FPGA integrated SoCs can provide the ideal trade-off between performance, adaptability, and energy usage. One of today’s vital challenges lies in updating existing fault tolerance techniques for these new systems while utilizing all available processing capa bilities, such as multi-core and heterogeneous processing units. Control-flow monitoring is one of the primary mechanisms described for error detection at the software architectural level for the highest grade of hazard level clas sifications (e.g., ASIL D) described in industry safety standards ISO-26262. Control-flow errors are also known to compose the majority of detected errors for ICs and embedded systems in safety-critical and risk-susceptible environ ments [5]. Software-based monitoring methods remain the most popular [6–8]. However, recent studies show that the overheads they impose make actual reliability gains negligible [9, 10]. This work proposes and demonstrates a new control flow checking method implemented in FPGA for multi-core embedded systems called control-flow trace checker (CFTC). CFTC uses existing trace and debug subsystems of modern processors to rebuild their execution states. It can iden tify any errors in real-time by comparing executed states to a set of permitted state transitions determined statically. This novel implementation weighs hardware resource trade-offs to target mul tiple independent tasks in multi-core embedded applications, as well as single core systems. The proposed system is entirely implemented in hardware and isolated from all monitored software components, requiring 2.4% of the target FPGA platform resources to protect an execution unit in its entirety. There fore, it avoids undesired overheads and maintains deterministic error detection latencies, which guarantees reliability improvements without impairing the target software system. Finally, CFTC is evaluated under different software i Resumo fault-injection scenarios, achieving detection rates of 100% of all control-flow errors to wrong destinations and 98% of all injected faults to program binaries. All detection times are further analyzed and precisely described by a model based on the monitor’s resources and speed and the software application’s control-flow structure and binary characteristics.Circuitos integrados estão presentes em quase todos sistemas complexos do mundo moderno. Conforme sua frequência de uso aumenta, eles precisam se tornar mais seguros e performantes para conseguir atender as novas demandas em potência de processamento. Sistemas em Chip integrados com FPGAs conseguem prover o balanço perfeito entre desempenho, adaptabilidade, e uso de energia. Um dos maiores desafios agora é a necessidade de atualizar técnicas de tolerância à falhas para estes novos sistemas, aproveitando os novos avanços em capacidade de processamento. Monitoramento de fluxo de controle é um dos principais mecanismos para a detecção de erros em nível de software para sistemas classificados como de alto risco (e.g. ASIL D), descrito em padrões de segurança como o ISO-26262. Estes erros são conhecidos por compor a maioria dos erros detectados em sistemas integrados [5]. Embora métodos de monitoramento baseados em software continuem sendo os mais populares [6–8], estudos recentes mostram que seus custos adicionais, em termos de performance e área, diminuem consideravelmente seus ganhos reais em confiabilidade [9, 10]. Propomos aqui um novo método de monitora mento de fluxo de controle implementado em FPGA para sistemas embarcados multi-core. Este método usa subsistemas de trace e execução de código para reconstruir o estado atual do processador, identificando erros através de com parações entre diferentes estados de execução da CPU. Propomos uma implementação que considera trade-offs no uso de recuros de sistema para monitorar múltiplas tarefas independetes. Nossa abordagem suporta o monitoramento de sistemas simples e também de sistemas multi-core multitarefa. Por fim, nossa técnica é totalmente implementada em hardware, evitando o uso de unidades de processamento de software que possa adicionar custos indesejáveis à aplicação em perda de confiabilidade. Propomos, assim, um mecanismo de verificação de fluxo de controle, escalável e extensível, para proteção de sistemas embarcados críticos e multi-core

Real-time trace decoding and monitoring for safety and security in embedded systems

Integrated circuits and systems can be found almost everywhere in today’s world. As their use increases, they need to be made safer and more perfor mant to meet current demands in processing power. FPGA integrated SoCs can provide the ideal trade-off between performance, adaptability, and energy usage. One of today’s vital challenges lies in updating existing fault tolerance techniques for these new systems while utilizing all available processing capa bilities, such as multi-core and heterogeneous processing units. Control-flow monitoring is one of the primary mechanisms described for error detection at the software architectural level for the highest grade of hazard level clas sifications (e.g., ASIL D) described in industry safety standards ISO-26262. Control-flow errors are also known to compose the majority of detected errors for ICs and embedded systems in safety-critical and risk-susceptible environ ments [5]. Software-based monitoring methods remain the most popular [6–8]. However, recent studies show that the overheads they impose make actual reliability gains negligible [9, 10]. This work proposes and demonstrates a new control flow checking method implemented in FPGA for multi-core embedded systems called control-flow trace checker (CFTC). CFTC uses existing trace and debug subsystems of modern processors to rebuild their execution states. It can iden tify any errors in real-time by comparing executed states to a set of permitted state transitions determined statically. This novel implementation weighs hardware resource trade-offs to target mul tiple independent tasks in multi-core embedded applications, as well as single core systems. The proposed system is entirely implemented in hardware and isolated from all monitored software components, requiring 2.4% of the target FPGA platform resources to protect an execution unit in its entirety. There fore, it avoids undesired overheads and maintains deterministic error detection latencies, which guarantees reliability improvements without impairing the target software system. Finally, CFTC is evaluated under different software i Resumo fault-injection scenarios, achieving detection rates of 100% of all control-flow errors to wrong destinations and 98% of all injected faults to program binaries. All detection times are further analyzed and precisely described by a model based on the monitor’s resources and speed and the software application’s control-flow structure and binary characteristics.Circuitos integrados estão presentes em quase todos sistemas complexos do mundo moderno. Conforme sua frequência de uso aumenta, eles precisam se tornar mais seguros e performantes para conseguir atender as novas demandas em potência de processamento. Sistemas em Chip integrados com FPGAs conseguem prover o balanço perfeito entre desempenho, adaptabilidade, e uso de energia. Um dos maiores desafios agora é a necessidade de atualizar técnicas de tolerância à falhas para estes novos sistemas, aproveitando os novos avanços em capacidade de processamento. Monitoramento de fluxo de controle é um dos principais mecanismos para a detecção de erros em nível de software para sistemas classificados como de alto risco (e.g. ASIL D), descrito em padrões de segurança como o ISO-26262. Estes erros são conhecidos por compor a maioria dos erros detectados em sistemas integrados [5]. Embora métodos de monitoramento baseados em software continuem sendo os mais populares [6–8], estudos recentes mostram que seus custos adicionais, em termos de performance e área, diminuem consideravelmente seus ganhos reais em confiabilidade [9, 10]. Propomos aqui um novo método de monitora mento de fluxo de controle implementado em FPGA para sistemas embarcados multi-core. Este método usa subsistemas de trace e execução de código para reconstruir o estado atual do processador, identificando erros através de com parações entre diferentes estados de execução da CPU. Propomos uma implementação que considera trade-offs no uso de recuros de sistema para monitorar múltiplas tarefas independetes. Nossa abordagem suporta o monitoramento de sistemas simples e também de sistemas multi-core multitarefa. Por fim, nossa técnica é totalmente implementada em hardware, evitando o uso de unidades de processamento de software que possa adicionar custos indesejáveis à aplicação em perda de confiabilidade. Propomos, assim, um mecanismo de verificação de fluxo de controle, escalável e extensível, para proteção de sistemas embarcados críticos e multi-core

An efficient logic fault diagnosis framework based on effect-cause approach

Fault diagnosis plays an important role in improving the circuit design process and the manufacturing yield. With the increasing number of gates in modern circuits, determining the source of failure in a defective circuit is becoming more and more challenging. In this research, we present an efficient effect-cause diagnosis framework for combinational VLSI circuits. The framework consists of three stages to obtain an accurate and reasonably precise diagnosis. First, an improved critical path tracing algorithm is proposed to identify an initial suspect list by backtracing from faulty primary outputs toward primary inputs. Compared to the traditional critical path tracing approach, our algorithm is faster and exact. Second, a novel probabilistic ranking model is applied to rank the suspects so that the most suspicious one will be ranked at or near the top. Several fast filtering methods are used to prune unrelated suspects. Finally, to refine the diagnosis, fault simulation is performed on the top suspect nets using several common fault models. The difference between the observed faulty behavior and the simulated behavior is used to rank each suspect. Experimental results on ISCAS85 benchmark circuits show that this diagnosis approach is efficient both in terms of memory space and CPU time and the diagnosis results are accurate and reasonably precise