We develop a microprocessor design that tolerates hard faults, including fabrication defects and in-field faults, by leveraging existing microprocessor redundancy. To do this, we must: detect and correct errors, diagnose hard faults at the field deconfigurable unit (FDU) granularity, and deconfigure FDUs with hard faults. In our reliable microprocessor design, we use DIVA dynamic verification to detect and correct errors. Our new scheme for diagnosing hard faults tracks instructions' core structure occupancy from decode until commit. If a DIVA checker detects an error in an instruction, it increments a small saturating error counter for every FDU used by that instruction, including that DIVA checker. A hard fault in an FDU quickly leads to an above-threshold error counter for that FDU and thus diagnoses the fault. For deconfiguration, we use previously developed schemes for functional units and buffers and present a scheme for deconfiguring DIVA checkers. Experimental results show that our reliable microprocessor quickly and accurately diagnoses each hard fault that is injected and continues to function, albeit with somewhat degraded performance.

We develop a microprocessor design that tolerates hard faults, including fabrication defects and in-field faults, by leveraging existing microprocessor redundancy. To do this, we must: detect and correct errors, diagnose hard faults at the field deconfigurable unit (FDU) granularity, and deconfigure FDUs with hard faults. In our reliable microprocessor design, we use DIVA dynamic verification to detect and correct errors. Our new scheme for diagnosing hard faults tracks instructions' core structure occupancy from decode until commit. If a DIVA checker detects an error in an instruction, it increments a small saturating error counter for every FDU used by that instruction, including that DIVA checker. A hard fault in an FDU quickly leads to an above-threshold error counter for that FDU and thus diagnoses the fault. For deconfiguration, we use previously developed schemes for functional units and buffers, and we present a scheme for deconfiguring DIVA checkers. Experimental results show that our reliable microprocessor quickly and accurately diagnoses each hard fault that is injected and continues to function, albeit with somewhat degraded performance.

To achieve high reliability despite hard faults that occur during operation and to achieve high yield despite defects introduced at fabrication, a microprocessor must be able to tolerate hard faults. In this paper, we present a framework for autonomic self-repair of the array structures in microprocessors (e.g., reorder buffer, instruction window, etc.). The framework consists of three aspects: 1) detecting/diagnosing the fault, 2) recovering from the resultant error, and 3) mapping out the faulty portion of the array. For each aspect, we present design options. Based on this framework, we develop two particular schemes for self-repairing array structures (SRAS). Simulation results show that one of our SRAS schemes adds some performance overhead in the fault-free case, but that both of them mask hard faults 1) with less hardware overhead cost than higher-level redundancy (e.g., IBM mainframes) and 2) without the per-error performance penalty of existing low-cost techniques that combine error detection with pipeline flushes for backward error recovery (BER). When hard faults are present in arrays, due to operational faults or fabrication defects, SRAS schemes outperform BER due to not having to frequently flush the pipeline.

In this paper, we present a hardware technique, called self-repairing array structures (SRAS), for masking hard faults in microprocessor array structures, such as the reorder buffer and branch history table. SRAS masks errors that could otherwise lead to slow system recoveries. To detect row errors, every write to a row is mirrored to a dedicated "check row". We then read out both the written row and check row and compare their results. To correct errors, SRAS maps out faulty array rows with a level of indirection.