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Hardware-assisted instruction profiling and latency detection

Suchakrapani Datt Sharma et Michel Dagenais

Article de revue (2016)

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Abstract

Debugging and profiling tools can alter the execution flow or timing, can induce heisenbugs and are thus marginally useful for debugging time critical systems. Software tracing, however advanced it may be, depends on consuming precious computing resources. In this study, the authors analyse state-of-the-art hardware-tracing support, as provided in modern Intel processors and propose a new technique which uses the processor hardware for tracing without any code instrumentation or tracepoints. They demonstrate the utility of their approach with contributions in three areas - syscall latency profiling, instruction profiling and software-tracer impact detection. They present improvements in performance and the granularity of data gathered with hardware-assisted approach, as compared with traditional software only tracing and profiling. The performance impact on the target system – measured as time overhead – is on average 2–3%, with the worst case being 22%. They also define a way to measure and quantify the time resolution provided by hardware tracers for trace events, and observe the effect of finetuning hardware tracing for optimum utilisation. As compared with other in-kernel tracers, they observed that hardware-based tracing has a much reduced overhead, while achieving greater precision. Moreover, the other tracing techniques are ineffective in certain tracing scenarios.

Mots clés

program debugging, program diagnostics, latency detection, syscall latency profiling, fine-tuning hardware tracing, hardware-assisted instruction profiling, hardware-based tracing, software tracing, sixth generation Intel processors, optimum utilisation, programming support Diagnostic testing, debugging and evaluating systems

Sujet(s): 2700 Technologie de l'information > 2700 Technologie de l'information
2700 Technologie de l'information > 2715 Optimisation
Département: Département de génie informatique et génie logiciel
Organismes subventionnaires: CRSNG/NSERC, Ericsson Software Research, EfficiOS, Prompt
URL de PolyPublie: https://publications.polymtl.ca/3068/
Titre de la revue: The Journal of Engineering (vol. 2016, no 10)
Maison d'édition: IET
DOI: 10.1049/joe.2016.0127
URL officielle: https://doi.org/10.1049/joe.2016.0127
Date du dépôt: 04 mai 2018 16:18
Dernière modification: 10 avr. 2024 16:15
Citer en APA 7: Sharma, S. D., & Dagenais, M. (2016). Hardware-assisted instruction profiling and latency detection. The Journal of Engineering, 2016(10), 367-376. https://doi.org/10.1049/joe.2016.0127

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