Monitoring and Debugging the Quality of Results in Approximate Programs

RingenburgMichael,; SampsonAdrian,; AckermanIsaac,; CezeLuis,; GrossmanDan,

doi:10.1145/2775054.2694365

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…The first part of the process involves identifying which instructions and data in the application can be treated as approximate. This is the responsibility of the programmer, as expert knowledge in the algorithm and the output error tolerance is required, but tools to help that process exist [38,47]. For our evaluation, we use benchmarks from the ACCEPT suite, which come annotated with which data can be approximate and which not.…”

Section: Methodsmentioning

confidence: 99%

“…Previous work [38,47] has developed frameworks for tracking which variables and errors affect the application, but not on the level of tracking individual random bit errors and correlating them with the final output. The computational resources required for such a task would be significantly greater, making the approach impractical when a large number of program executions is required.…”

Section: Evaluation Of Potential Applicationsmentioning

confidence: 99%

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Evaluating the Potential Applications of Quaternary Logic for Approximate Computing

Sakalis

Jimborean

Själander

2019

J. Emerg. Technol. Comput. Syst.

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There exist extensive ongoing research efforts on emerging atomic-scale technologies that have the potential to become an alternative to today’s complementary metal--oxide--semiconductor technologies. A common feature among the investigated technologies is that of multi-level devices, particularly the possibility of implementing quaternary logic gates and memory cells. However, for such multi-level devices to be used reliably, an increase in energy dissipation and operation time is required. Building on the principle of approximate computing, we present a set of combinational logic circuits and memory based on multi-level logic gates in which we can trade reliability against energy efficiency. Keeping the energy and timing constraints constant, important data are encoded in a more robust binary format while error-tolerant data are encoded in a quaternary format. We analyze the behavior of the logic circuits when exposed to transient errors caused as a side effect of this encoding. We also evaluate the potential benefit of the logic circuits and memory by embedding them in a conventional computer system on which we execute jpeg, sobel, and blackscholes approximately. We demonstrate that blackscholes is not suitable for such a system and explain why. However, we also achieve dynamic energy reductions of 10% and 13% for jpeg and sobel, respectively, and improve execution time by 38% for sobel, while maintaining adequate output quality.

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Section: Methodsmentioning

confidence: 99%

Section: Evaluation Of Potential Applicationsmentioning

confidence: 99%

Evaluating the Potential Applications of Quaternary Logic for Approximate Computing

Sakalis

Jimborean

Själander

2019

J. Emerg. Technol. Comput. Syst.

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“…Languages support approximation allowing specification of variants for key functionality and formal analysis of their effects [11]- [13], [15], [16], [42]- [45]. Other mechanisms guarantee that approximate programs will maintain some quality or energy guarantees either through program analysis [46]- [48] or runtimes with formally analyzable dynamic adaptation [37], [49]- [55].…”

Section: Motivation and Backgroundmentioning

confidence: 99%

Comparing and Combining Approximate Computing Frameworks

Barati,

Kindlmann,

Hoffmann

2021

Preprint

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Approximate computing frameworks configure applications so they can operate at a range of points in an accuracyperformance trade-off space. Prior work has introduced many frameworks to create approximate programs. As approximation frameworks proliferate, it is natural to ask how they can be compared and combined to create even larger, richer trade-off spaces. We address these questions by presenting VIPER and BOA. VIPER compares trade-off spaces induced by different approximation frameworks by visualizing performance improvements across the full range of possible accuracies. BOA is a family of exploration techniques that quickly locate Pareto-efficient points in the immense trade-off space produced by the combination of two or more approximation frameworks. We use VIPER and BOA to compare and combine three different approximation frameworks from across the system stack, including: one that changes numerical precision, one that skips loop iterations, and one that manipulates existing application parameters. Compared to simply looking at Pareto-optimal curves, we find VIPER's visualizations provide a quicker and more convenient way to determine the best approximation technique for any accuracy loss. Compared to a state-of-the-art evolutionary algorithm, we find that BOA explores 14× fewer configurations yet locates 35% more Pareto-efficient points.

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Approximate Computing: A Survey of Recent Trends—Bringing Greenness to Computing and Communication

Barua

Mondal

2019

J. Inst. Eng. India Ser. B

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Monitoring and Debugging the Quality of Results in Approximate Programs

Cited by 7 publications

References 25 publications

Evaluating the Potential Applications of Quaternary Logic for Approximate Computing

Evaluating the Potential Applications of Quaternary Logic for Approximate Computing

Comparing and Combining Approximate Computing Frameworks

Approximate Computing: A Survey of Recent Trends—Bringing Greenness to Computing and Communication

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