Automatic Instruction-Level Software-Only Recovery

Chang, Jonathan; Reis, George A.; August, David I.

doi:10.1109/dsn.2006.15

Cited by 88 publications

(60 citation statements)

References 24 publications

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“…For all approaches the error injection experiments show a non-negligible amount of undetected failures. This is even higher for [10] and [7] because the used encoding is incomplete.…”

Section: Related Workmentioning

confidence: 97%

“…Therefore, the program and the processed data are modified. ANencoding was already used by [10,7,14]. For all approaches the error injection experiments show a non-negligible amount of undetected failures.…”

Section: Related Workmentioning

confidence: 99%

“…Replication is applied at different levels of abstraction. Some approaches duplicate single instructions within one thread, e. g., [7,11,4]. Others execute duplicates of the whole program using several threads, e. g., [16].…”

Section: Related Workmentioning

confidence: 99%

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ANB- and ANBDmem-Encoding: Detecting Hardware Errors in Software

Schiffel

Schmitt

Süßkraut

et al. 2010

Lecture Notes in Computer Science

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Abstract. It is expected that commodity hardware is becoming less reliable because of the continuously decreasing feature sizes of integrated circuits. Nevertheless, more and more commodity hardware with insufficient error detection is used in critical applications. One possible solution is to detect hardware errors in software using arithmetic AN-codes. These codes detect hardware errors independent of the actual failure modes of the underlying hardware. However, measurements have shown that AN-codes still exhibit large rates of undetected silent data corruptions (SDC). These high rates of undetected SDCs are caused by the insufficient protection of control and data flow through AN-codes. In contrast, ANB-and ANBD-codes promise much higher error detection rates because they also detect errors in control and data flow. We present our encoding compiler that automatically applies either an AN-, ANBor ANBD-code to an application. Our error injections show that AN-, ANB-, and ANBD-codes successfully detect errors and more important that indeed ANB-and ANBD-codes reduce the SDC rate more effectively than AN-codes. The difference between ANBD-and ANB-codes is also visible but less pronounced.

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“…For all approaches the error injection experiments show a non-negligible amount of undetected failures. This is even higher for [10] and [7] because the used encoding is incomplete.…”

Section: Related Workmentioning

confidence: 97%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

ANB- and ANBDmem-Encoding: Detecting Hardware Errors in Software

Schiffel

Schmitt

Süßkraut

et al. 2010

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…Replication can be implemented at different levels of abstraction. Some approaches duplicate single instructions and execute them in one thread [22,19,10,25,24,6]. Other approaches execute duplicates of the whole program within several threads and provide synchronization means for them [31,12,32].…”

Section: Related Workmentioning

confidence: 99%

“…3). In contrast to similar previous approaches such as [20,10,34], we encode the whole application with the same powerful code. This includes memory, logical operations, and handling of external functions whose source code is not available for encoding.…”

Section: Introductionmentioning

confidence: 99%

AN-Encoding Compiler: Building Safety-Critical Systems with Commodity Hardware

Fetzer

Schiffel

Süßkraut

2009

Lecture Notes in Computer Science

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Abstract. In the future, we expect commodity hardware to be used in safety-critical applications. However, in the future commodity hardware is expected to become less reliable and more susceptible to soft errors because of decreasing feature size and reduced power supply. Thus, software-implemented approaches to deal with unreliable hardware will be needed. To simplify the handling of value failures, we provide failure virtualization in the sense that we transform arbitrary value failures caused by erroneous execution into fail-stop failures. The latter ones are easier to handle. Therefore, we use the arithmetic AN-code because it provides very good error detection capabilities. Arithmetic codes are suitable for the protection of commodity hardware because guarantees can be provided independent of the executing hardware. This paper presents the encoding compiler EC-AN which applies AN-encoding to arbitrary programs. According to our knowledge, this is the first in software implemented complete AN-encoding. Former encoding compilers either encode only small parts of applications or trade-off safety to enable complete AN-encoding.

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Hybrid Fault Tolerance Techniques to Detect Transient Faults in Embedded Processors

Azambuja

Kastensmidt

Becker

2014

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The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.

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Automatic Instruction-Level Software-Only Recovery

Cited by 88 publications

References 24 publications

ANB- and ANBDmem-Encoding: Detecting Hardware Errors in Software

ANB- and ANBDmem-Encoding: Detecting Hardware Errors in Software

AN-Encoding Compiler: Building Safety-Critical Systems with Commodity Hardware

Hybrid Fault Tolerance Techniques to Detect Transient Faults in Embedded Processors

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