2013
DOI: 10.1145/2536747.2536753
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Improving the fault resilience of an H.264 decoder using static analysis methods

Abstract: Fault tolerance rapidly evolves into one of the most significant design objectives for embedded systems due to reduced semiconductor structures and supply voltages. However, resource-constrained systems cannot afford traditional error correction for overhead and cost reasons. New methods are required to sustain acceptable service quality in case of errors while avoiding crashes.We present a flexible fault-tolerance approach that is able to select correction actions depending on error semantics using applicatio… Show more

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Cited by 20 publications
(11 citation statements)
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“…Gschwandtner et al use a similar iterative approach to execute error-tolerant solvers on processors that operate with near-threshold voltage (NTC) and reduce energy consumption by replacing cores operating at nominal voltage with NTC cores [4]. Schmoll et al [16] present algorithmic and static analysis techniques to detect variables that must be computed reliably and variables that can be computed approximately in an H.264 video decoder. Although we follow a domain-agnostic approach in our approximate computing framework, we provide sufficient abstractions for implementing the aforementioned application-specific approximation methods.…”
Section: Other Approximation Frameworkmentioning
confidence: 99%
“…Gschwandtner et al use a similar iterative approach to execute error-tolerant solvers on processors that operate with near-threshold voltage (NTC) and reduce energy consumption by replacing cores operating at nominal voltage with NTC cores [4]. Schmoll et al [16] present algorithmic and static analysis techniques to detect variables that must be computed reliably and variables that can be computed approximately in an H.264 video decoder. Although we follow a domain-agnostic approach in our approximate computing framework, we provide sufficient abstractions for implementing the aforementioned application-specific approximation methods.…”
Section: Other Approximation Frameworkmentioning
confidence: 99%
“…The authors of [29] and [31] introduce programming techniques to exploit unreliable memories by distinguishing reliable and unreliable data types.…”
Section: A Approximate Dram -Reliability Vs Powermentioning
confidence: 99%
“…Contrary to approximation techniques via loop perforation implemented in the compiler [13], our programming model uses domain expertise available from the programmer, which we demonstrate to be necessary for effective approximation in at least one application domain. On the other hand, our programming model remains general-purpose, contrary to applicationspecific approximate code generators such as SAGE [10], Paraprox [9] ApproxIt [20] and related work on iterative solvers [4] and video codecs [12]. Compared to other approximate language frameworks such as EnerJ [11], our programming model offers additional features including task-parallel execution and energy-constrained runtime optimization of output quality.…”
Section: Related Workmentioning
confidence: 99%