5 research outputs found

    Fault tolerant methods for reliability in FPGAs

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    Characterisation and mitigation of long-term degradation effects in programmable logic

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    Reliability has always been an issue in silicon device engineering, but until now it has been managed by the carefully tuned fabrication process. In the future the underlying physical limitations of silicon-based electronics, plus the practical challenges of manufacturing with such complexity at such a small scale, will lead to a crunch point where transistor-level reliability must be forfeited to continue achieving better productivity. Field-programmable gate arrays (FPGAs) are built on state-of-the-art silicon processes, but it has been recognised for some time that their distinctive characteristics put them in a favourable position over application-specific integrated circuits in the face of the reliability challenge. The literature shows how a regular structure, interchangeable resources and an ability to reconfigure can all be exploited to detect, locate, and overcome degradation and keep an FPGA application running. To fully exploit these characteristics, a better understanding is needed of the behavioural changes that are seen in the resources that make up an FPGA under ageing. Modelling is an attractive approach to this and in this thesis the causes and effects are explored of three important degradation mechanisms. All are shown to have an adverse affect on FPGA operation, but their characteristics show novel opportunities for ageing mitigation. Any modelling exercise is built on assumptions and so an empirical method is developed for investigating ageing on hardware with an accelerated-life test. Here, experiments show that timing degradation due to negative-bias temperature instability is the dominant process in the technology considered. Building on simulated and experimental results, this work also demonstrates a variety of methods for increasing the lifetime of FPGA lookup tables. The pre-emptive measure of wear-levelling is investigated in particular detail, and it is shown by experiment how di fferent reconfiguration algorithms can result in a significant reduction to the rate of degradation

    Dynamic partial reconfiguration management for high performance and reliability in FPGAs

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    Modern Field-Programmable Gate Arrays (FPGAs) are no longer used to implement small “glue logic” circuitries. The high-density of reconfigurable logic resources in today’s FPGAs enable the implementation of large systems in a single chip. FPGAs are highly flexible devices; their functionality can be altered by simply loading a new binary file in their configuration memory. While the flexibility of FPGAs is comparable to General-Purpose Processors (GPPs), in the sense that different functions can be performed using the same hardware, the performance gain that can be achieved using FPGAs can be orders of magnitudes higher as FPGAs offer the ability for customisation of parallel computational architectures. Dynamic Partial Reconfiguration (DPR) allows for changing the functionality of certain blocks on the chip while the rest of the FPGA is operational. DPR has sparked the interest of researchers to explore new computational platforms where computational tasks are off-loaded from a main CPU to be executed using dedicated reconfigurable hardware accelerators configured on demand at run-time. By having a battery of custom accelerators which can be swapped in and out of the FPGA at runtime, a higher computational density can be achieved compared to static systems where the accelerators are bound to fixed locations within the chip. Furthermore, the ability of relocating these accelerators across several locations on the chip allows for the implementation of adaptive systems which can mitigate emerging faults in the FPGA chip when operating in harsh environments. By porting the appropriate fault mitigation techniques in such computational platforms, the advantages of FPGAs can be harnessed in different applications in space and military electronics where FPGAs are usually seen as unreliable devices due to their sensitivity to radiation and extreme environmental conditions. In light of the above, this thesis investigates the deployment of DPR as: 1) a method for enhancing performance by efficient exploitation of the FPGA resources, and 2) a method for enhancing the reliability of systems intended to operate in harsh environments. Achieving optimal performance in such systems requires an efficient internal configuration management system to manage the reconfiguration and execution of the reconfigurable modules in the FPGA. In addition, the system needs to support “fault-resilience” features by integrating parameterisable fault detection and recovery capabilities to meet the reliability standard of fault-tolerant applications. This thesis addresses all the design and implementation aspects of an Internal Configuration Manger (ICM) which supports a novel bitstream relocation model to enable the placement of relocatable accelerators across several locations on the FPGA chip. In addition to supporting all the configuration capabilities required to implement a Reconfigurable Operating System (ROS), the proposed ICM also supports the novel multiple-clone configuration technique which allows for cloning several instances of the same hardware accelerator at the same time resulting in much shorter configuration time compared to traditional configuration techniques. A faulttolerant (FT) version of the proposed ICM which supports a comprehensive faultrecovery scheme is also introduced in this thesis. The proposed FT-ICM is designed with a much smaller area footprint compared to Triple Modular Redundancy (TMR) hardening techniques while keeping a comparable level of fault-resilience. The capabilities of the proposed ICM system are demonstrated with two novel applications. The first application demonstrates a proof-of-concept reliable FPGA server solution used for executing encryption/decryption queries. The proposed server deploys bitstream relocation and modular redundancy to mitigate both permanent and transient faults in the device. It also deploys a novel Built-In Self- Test (BIST) diagnosis scheme, specifically designed to detect emerging permanent faults in the system at run-time. The second application is a data mining application where DPR is used to increase the computational density of a system used to implement the Frequent Itemset Mining (FIM) problem
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