ACE analysis is a technique to provide an early reliability estimate for microprocessors. ACE analysis couples data from abstract performance models with low level design details to identify and rule out transient faults that will not cause incorrect execution. While many transient faults are analyzable in ACE analysis frameworks, some are not. As a result, ACE analysis is conservative and provides a lower bound for the reliability of a processor design. Bounding the reliability of a design is useful since it can guarantee that the given design will meet reliability goals.

Device scaling and large-scale integration have led to growing concerns about soft errors in microprocessors. To date, in all but the most demanding applications, implementing parity and ECC for caches and other large, regular SRAM structures have been sufficient to stem the growing soft error tide. This will not be the case for long and questions remain as to the best way to detect and recover from soft errors in the remainder of the processor - in particular, the less structured execution core. In this work, we propose the ReStore architecture, which leverages existing performance enhancing checkpointing hardware to recover from soft error events in a low cost fashion. Error detection in the ReStore architecture is novel: symptoms that hint at the presence of soft errors trigger restoration of a previous checkpoint. Example symptoms include exceptions, control flow misspeculations, and cache or translation look-aside buffer misses. Compared to conventional soft error detection via full replication, the ReStore framework incurs little overhead, but sacrifices some amount of error coverage. These attributes make it an ideal means to provide very cost effective error coverage for processor applications that can tolerate a nonzero, but small, soft error failure rate. Our evaluation of an example ReStore implementation exhibits a 2times increase in MTBF (mean time between failures) over a standard pipeline with minimal hardware and performance overheads. The MTBF increases by 20times if ReStore is coupled with protection for certain particularly vulnerable pipeline structures

This paper presents a built-in soft error resilience (BISER) technique for correcting radiation-induced soft errors in latches and flip-flops. The presented error-correcting latch and flip-flop designs are power efficient, introduce minimal speed penalty, and employ reuse of on-chip scan design-for-testability and design-for-debug resources to minimize area overheads. Circuit simulations using a sub-90-nm technology show that the presented designs achieve more than a 20-fold reduction in cell-level soft error rate (SER). Fault injection experiments conducted on a microprocessor model further demonstrate that chip-level SER improvement is tunable by selective placement of the presented error-correcting designs. When coupled with error correction code to protect in-pipeline memories, the BISER flip-flop design improves chip-level SER by 10 times over an unprotected pipeline with the flip-flops contributing an extra 7-10.5% in power. When only soft errors in flips-flops are considered, the BISER technique improves chip-level SER by 10 times with an increased power of 10.3%. The error correction mechanism is configurable (i.e., can be turned on or off) which enables the use of the presented techniques for designs that can target multiple applications with a wide range of reliability requirements

Device scaling and large scale integration have led to growing concerns about soft errors in microprocessors. To date, in all but the most demanding applications, implementing parity and ECC for caches and other large, regular SRAM structures have been sufficient to stem the growing soft error tide. This will not be the case for long, and questions remain as to the best way to detect and recover from soft errors in the remainder of the processor - in particular, the less structured execution core. In this work, we propose the ReStore architecture, which leverages existing performance enhancing checkpointing hardware to recover from soft error events in a low cost fashion. Error detection in the ReStore architecture is novel: symptoms that hint at the presence of soft errors trigger restoration of a previous checkpoint. Example symptoms include exceptions, control flow mis-speculations, and cache or translation look-aside buffer misses. Compared to conventional soft error detection via full replication, the ReStore framework incurs little overhead, but sacrifices some amount of error coverage. These attributes make it an ideal means to provide very cost effective error coverage for processor applications that can tolerate a nonzero, but small, soft error failure rate. Our evaluation of an example ReStore implementation exhibits a 2x increase in MTBE (mean time between failures) over a standard pipeline with minimal hardware and performance overheads. The MTBF increases by 7x if ReStore is coupled with parity protection for certain pipeline structures.

The progression of implementation technologies into the sub-100 nanometer lithographies renew the importance of understanding and protecting against single-event upsets in digital systems. In this work, the effects of transient faults on high performance microprocessors is explored. To perform a thorough exploration, a highly detailed register transfer level model of a deeply pipelined, out-of-order microprocessor was created. Using fault injection, we determined that fewer than 15% of single bit corruptions in processor state result in software visible errors. These failures were analyzed to identify the most vulnerable portions of the processor, which were then protected using simple low-overhead techniques. This resulted in a 75% reduction in failures. Building upon the failure modes seen in the microarchitecture, fault injections into software were performed to investigate the level of masking that the software layer provides. Together, the baseline microarchitectural substrate and software mask more than 9 out of 10 transient faults from affecting correct program execution.