Hamid R. Zarandi

Dependability analysis using a fault injection tool based on synthesizability of HDL models

This paper presents a fault injection tool called SINJECT that supports several synthesizable and non-synthesizable fault models for dependability analysis of digital systems modeled by popular HDLs. The tool provides injection of transient and permanent faults into the Verilog as well as VHDL models of a digital circuit to study the fault behavior, fault propagation and fault coverage. Moreover, using specific simulators, the SINJECT provides a mixed-mode fault injection, i.e., fault injection into both Verilog and VHDL parts of a model, to achieve high description reality by Verilog and high capability modeling by VHDL. To demonstrate the tool, two case studies are evaluated: (1) an arithmetic processor with a non-synthesizable Verilog model, called ARP; and (2) a VHDL model of 32-bit processor with a synthesizable ALU, called DP32. The results show that depending on the fault injection points in the ARP, the effects of faults were significantly different, while in the case of DP32, the fault coverage varied between 51 to 56 percent of total faults injected.

Matrix Codes: Multiple Bit Upsets Tolerant Method for SRAM Memories

This paper presents a high level method called Matrix code to protect SRAM-based memories against multiple bit upsets. The proposed method combines hamming code and parity code to assure the reliability of memory in presence of multiple bit-upsets with low area and performance overhead. The method is evaluated using one million multiple-fault injection experiments; next reliability and MTTF of the protected memories are estimated based on fault injection experiments and several equations. The fault detection/correction coverage are also calculated and compared with previous methods i.e., Reed-Muller and hamming code. The results reveal that the proposed method behaves better than these methods in terms of fault detection and correction of multiple faults regarding to the area overhead.

A Fast and Accurate Fault Tree Analysis Based on Stochastic Logic Implemented on Field-Programmable Gate Arrays

This paper presents a method based on stochastic logic to analyse fault trees. This method supports both static and dynamic gates, and can be applied to any type of fault trees. In this paper, static and dynamic gates would be translated into stochastic logic templates, and a hardware implementation for each gate would be achieved. Based on these hardware templates, it is possible to implement the whole logic on a Field-Programmable Gate Array (FPGA). Utilizing the stochastic logic for implementing a given fault tree on FPGA, the analysis would outperform the following parameters compared to traditional methods: 1) Speed-up, 2) Simplicity, 3) Reliability, and 4) Accuracy. Experimental results illustrate that using stochastic logic for modeling fault trees results in fast convergence of Monte Carlo simulation. Moreover, on average, our FPGA approach takes 50% of the time required by previous emulation approaches. Simplicity is an additional advantage of the proposed approach, achieved because of simplicity behind stochastic logic. Also, the stochastic logic is more reliable compared to traditional logic because any faults like SEUs in stochastic logic have less impact on the whole results compared to traditional arithmetic logic. To evaluate the proposed technique, the analysis is performed on several standard benchmarks composed of static and dynamic gates. The results obtained using this approach agree with those obtained from an analytical approach, which proves that the method is an accurate tool for system reliability modeling.

SEU-Mitigation Placement and Routing Algorithms and Their Impact in SRAM-Based FPGAs

In this paper, the authors propose a new SEU-mitigative placement and routing of circuits in the FPGAs which is based on the popular VPR tool. The VPR tool is modified so that during placement and routing, decisions are taken with awareness of SEU-mitigation. Moreover, no redundancies during the placement and routing are used but the algorithms are based on the SEU avoidance. Using the modified tool, i.e., S-VPR, the role of placement and routing algorithms on the fault-tolerance of circuits implemented on FPGAs is achieved. The secondary propose of this paper is to find which of placement or routing is more suited for decreasing SEU sensibility of circuits and to find whether these SEU sensibility reductions are cumulative or not when they applied in sequence. We have investigated the effect of S-VPR on several MCNC benchmarks and the results of the placement and routing have been compared to the traditional one. The evaluations of results show that placement and routing can decrease the SEU rate of circuits implemented on FPGAs about 18% and 12%, respectively. However, it increases critical path delay and power consumptions of the circuits up to 5% and 8%, respectively. This means that without any redundancies, just by means of fault-avoidance method, mitigation of SEU effects would decrease up to 22% significantly and this method is notable compared to previous TMR and DWC mechanisms

Fast SEU Detection and Correction in LUT Configuration Bits of SRAM-based FPGAs

FPGAs are an appealing solution for the space-based remote sensing applications. However, in a low-earth orbit, configuration bits of SRAM-based FPGAs are susceptible to single-event upsets (SEUs). In this paper, a new protected CLB and FPGA architecture are proposed which utilize error detection and correction codes to correct SEUs occurred in LUTs of the FPGA. The fault detection and correction is achieved using online or offline fast detection and correction cycles. In the latter, detection and correction is performed in predefined error-correction intervals. In both of them error detections and corrections of k-input LUTs are performed with a latency of 2k clock cycle without any required reconfiguration and significant area overhead. The power and area analysis of the proposed techniques show that these methods are more efficient than the traditional schemes such as duplication with comparison and TMR circuit design in the FPGAs.

Two Efficient Software Techniques to Detect and Correct Control-Flow Errors

This paper proposes two efficient software techniques, Control-flow and Data Errors Correction using Data-flow Graph Consideration (CDCC) and Miniaturized Check-Pointing (MCP), to detect and correct control-flow errors. These techniques have been implemented based on addition of redundant codes in a given program. The creativity applied in the methods for online detection and correction of the control-flow errors is using data-flow graph alongside of using control-flow graph. These techniques can detect most of the control-flow errors in the program firstly, and next can correct them, automatically. Therefore, both errors in the control-flow and program data which is caused by control-flow errors can be corrected, efficiently. In order to evaluate the proposed techniques, a post compiler is used, so that the techniques can be applied to every 80X86 binaries, transparently. Three benchmarks quick sort, matrix multiplication and linked list are used, and a total of 5000 transient faults are injected on several executable points in each program. The experimental results demonstrate that at least 93% and 89% of the control-flow errors can be detected and corrected without any data error generation by the CDCC and MCP, respectively. Moreover, the strength of these techniques is significant reduction in the performance and memory overheads in compare to traditional methods, for as much as remarkable correction abilities.

Dependability evaluation of Altera FPGA-based embedded systems subjected to SEUs

Dependability evaluation of embedded systems due to the integration of hardware and software parts is difficult to analyze. In this paper, we have proposed an experimental method to determine sensitivity to soft errors in an embedded system exploiting Altera SRAM-based FPGAs. The evaluation is performed using both the hardware and software parts of the embedded system in a single framework. To do this, the HDL hardware model of the target system as well as the C-written software codes of the target system, are required. Both permanent and transient faults are injected into the partially- or fully-synthesizable hardware of the target system and this can be performed during the design cycle of the system. The fault injection is composed of injecting SEUs into user design memory, and used configuration memory of the exploited FPGA. Using the experimental results, the sensitivity of Altera FPGAs to SEU faults are analyzed and derived. The analytical results reveal that the configuration memory is more significant than design memory to the SEUs due to the relative number of SRAM bits. Moreover, in this framework, in the case of injecting SEUs into user memory, the fault injection experiments are accelerated by the cooperation between a simulator and the FPGA.

Fault injection into verilog models for dependability evaluation of digital systems

This paper presents transient and permanent fault injection into Verilog models of digital systems during the design phase by a developed simulation-based fault injection tool called INJECT. With this fault injection tool, it is possible to inject crucial fault models in all abstraction levels (such as swith-level) supported by Verilog HDL. Several fault models for injecting into Verilog models are specified and described. Analyzing the results obtained from the fault injections, using INJECT enables system designers to inform from dependable parameters, such as fault latency, propagation and coverage. As a case study, a 32-bit processor, namely DP32, has been evaluated and effects of faults on some important observation points have been presented. In this study, recovered errors are distinguished from those that affected the system behavior. The errors that lead to wrong results are separated from those that do not affect the correct results.

Soft Error Mitigation in Switch Modules of SRAM-based FPGAs

In this paper, we propose two techniques to mitigate soft error effects on the switch modules of SRAM-based FPGAs: 1) The first technique tolerates SEU-caused open errors based on a new programming method for SRAM-bits of switch modules, and 2) The second technique mitigates SEU-cause short errors in the switch modules based on a mixed programmable and hard-wired switch module structure in the FPGAs. The effects of these two techniques on the delay, area and power consumption for 20 MCNC benchmark circuits are achieved using a minor modification in VPR and T-VPack FPGA CAD tools. The experimental results show that the first technique increase reliability of connections of switch module up to 30% while the second technique decreases the susceptibility of switch modules to SEUs about 50% compared to the traditional ones

A fault-tolerant core mapping technique in networks-on-chip

This study proposes a fault-tolerant technique on application mapping and spare core allocation in networks-on-chip. The proposed technique sets the place of spare cores among free non-faulty processing cores, dynamically. Here, dynamically setting means that the places of spare cores are tuned for each application and are not fixed in the platform statically. Some vertices of each application core graph can be known as critical, based on their vulnerabilities, the performance degradation and the energy consumption overheads because of negative impacts of failure recovery. This technique locates the spare cores near to the critical cores. As the main theoretical contribution, the problem of spare core placement and its impression on system fault-tolerance properties is discussed. Some metrics are investigated to be considered in spare core allocation. The results of 1 000 000 fault injection experiments show that the proposed technique leads to communication energy reductions and performance improvement, compared with related works.