nach oben

The Journal of Supercomputing

Erschienen in:

07.01.2022

Evaluating low-level software-based hardening techniques for configurable GPU architectures

verfasst von: Marcio M. Goncalves, Josie E. Rodriguez Condia, Matteo Sonza Reorda, Luca Sterpone, Jose Rodrigo Azambuja

Erschienen in: The Journal of Supercomputing | Ausgabe 6/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The high processing power of GPUs makes them attractive for safety-critical applications, where transient effects are a major concern, and resilience must be enforced without compromising performance. Configurable softcore GPUs are a recent technology that allows detailed reliability assessment capable of bringing directions to the design of reliable GPU applications. This work investigates the reliability of the register files and the pipeline of a softcore GPU under radiation-induced faults. It proposes software-based fault tolerance techniques to mitigate errors. Faults are simulated at the register transfer level in four case-study algorithms, and the Architectural Vulnerability Factor (AVF) and Mean Workload to Failure (MWTF) are checked over different GPU configurations. Results indicate that software-based techniques efficiently reduce AVF. In terms of MWTF, results show that the best cases depend on an optimized balance between GPU configuration, application runtime, and AVF.

Vorheriger Artikel Design and implementation of efficient QCA full-adders using fault-tolerant majority gates

Nächster Artikel A hybrid machine learning approach for detecting unprecedented DDoS attacks

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Chernikova A, Oprea A, Nita-Rotaru C, Kim B (2019) Are self-driving cars secure? Evasion attacks against deep neural networks for steering angle prediction. In: 2019 IEEE Security and Privacy Workshops (SPW), pp 132–137. https://doi.org/10.1109/SPW.2019.00033

Hassani R, Aiatullah M, Luksch P (2014) Improving HPC application performance in public cloud. IERI Procedia 10:169–176. https://doi.org/10.1016/j.ieri.2014.09.072CrossRef

Hakobyan G, Yang B (2019) High-performance automotive radar: a review of signal processing algorithms and modulation schemes. IEEE Signal Process Mag 36(5):32–44. https://doi.org/10.1109/MSP.2019.2911722CrossRef

Bojarski M, Del Testa D, Dworakowski D, Firner B, Flepp B, Goyal P, Jackel LD, Monfort M, Muller U, Zhang J et al (2016) End to end learning for self-driving cars. arXiv preprint arXiv:160407316

JEDEC (2006) Measurement and reporting of alpha particle and terrestrial cosmic ray induced soft errors in semiconductor devices. https://www.jedec.org/standards-documents/docs/jesd-89a. Accessed 19 Sept 2021

Oliveira DA, Rech P, Quinn HM, Fairbanks TD, Monroe L, Michalak SE, Anderson-Cook C, Navaux PO, Carro L (2014) Modern GPUs radiation sensitivity evaluation and mitigation through duplication with comparison. IEEE Trans Nucl Sci 61(6):3115–3122CrossRef

Pilla LL, Rech P, Silvestri F, Frost C, Navaux POA, Reorda MS, Carro L (2014) Software-based hardening strategies for neutron sensitive FFT algorithms on GPUs. IEEE Trans Nucl Sci 61(4):1874–1880CrossRef

Slayman C (2010) Soft errors—past history and recent discoveries. In: IEEE International Integrated Reliability Workshop Final Report, pp 25–30

Dixit A, Wood A (2011) The impact of new technology on soft error rates. In: International Reliability Physics Symposium, pp 1–7

10.

Azambuja JR, Nazar G, Rech P, Carro L, Kastensmidt FL, Fairbanks T, Quinn H (2013) Evaluating neutron induced see in SRAM-based FPGA protected by hardware- and software-based fault tolerant techniques. IEEE Trans Nucl Sci 60(6):4243–4250. https://doi.org/10.1109/TNS.2013.2288305CrossRef

11.

Tiwari D, Gupta S, Rogers J, Maxwell D, Rech P, Vazhkudai S, Oliveira D, Londo D, DeBardeleben N, Navaux P, Carro L, Bland A (2015) Understanding GPU errors on large-scale HPC systems and the implications for system design and operation. In: 2015 IEEE International Symposium on High Performance Computer Architecture (HPCA), pp 331–342. https://doi.org/10.1109/HPCA.2015.7056044

12.

Hari SKS, Tsai T, Stephenson M, Keckler SW, Emer J (2017) SASSIFI: an architecture-level fault injection tool for GPU application resilience evaluation. In: 2017 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), pp 249–258

13.

Gonçalves M, Saquetti M, Kastensmidt F, Azambuja JR (2017) A low-level software-based fault tolerance approach to detect SEUs in GPUs’ register files. Microelectron Reliab 76:665–669CrossRef

14.

Gonçalves M, Saquetti M, Azambuja JR (2018) Evaluating the reliability of a GPU pipeline to SEU and the impacts of software-based and hardware-based fault tolerance techniques. Microelectron Reliab 88:931–935CrossRef

15.

Mahmoud A, Hari SKS, Sullivan MB, Tsai T, Keckler SW (2018) Optimizing software-directed instruction replication for GPU error detection. In: SC18: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, pp 842–853

16.

Rhod EL, Lisbôa CAL, Carro L, Sonza Reorda M, Violante M (2008) Hardware and software transparency in the protection of programs against SEUs and SETs. J Electron Test 24(1–3):45–56CrossRef

17.

Condia JER, Du B, Sonza Reorda M, Sterpone L (2020) Flexgripplus: an improved GPGPU model to support reliability analysis. Microelectron Reliab 109:113660. https://doi.org/10.1016/j.microrel.2020.113660CrossRef

18.

Kadi MA, Janssen B, Yudi J, Huebner M (2018) General-purpose computing with soft GPUs on FPGAs. ACM Trans Reconfigurable Technol Syst 11(1):1–22. https://doi.org/10.1145/3173548CrossRef

19.

Goncalves MM, Azambuja JR, Condia JER, Sonza Reorda M, Sterpone L (2020) Evaluating software-based hardening techniques for general-purpose registers on a GPGPU. In: 2020 IEEE Latin-American Test Symposium (LATS). IEEE, pp 1–6

20.

Dimitrov M, Mantor M, Zhou H (2009) Understanding software approaches for GPGPU reliability. In: Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units, GPGPU-2. ACM, New York, pp 94–104. https://doi.org/10.1145/1513895.1513907

21.

Wadden J, Lyashevsky A, Gurumurthi S, Sridharan V, Skadron K (2014) Real-world design and evaluation of compiler-managed GPU redundant multithreading. In: 2014 ACM/IEEE 41st International Symposium on Computer Architecture (ISCA), pp 73–84. https://doi.org/10.1109/ISCA.2014.6853227

22.

Rech P, Aguiar C, Frost C, Carro L (2013) An efficient and experimentally tuned software-based hardening strategy for matrix multiplication on GPUs. IEEE Trans Nucl Sci 60(4):2797–2804CrossRef

23.

Braun C, Halder S, Wunderlich HJ (2014) A-abft: autonomous algorithm-based fault tolerance for matrix multiplications on graphics processing units. In: 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks. IEEE, pp 443–454

24.

Sullivan MB, Hari SKS, Zimmer B, Tsai T, Keckler SW (2018) Swapcodes: error codes for hardware-software cooperative GPU pipeline error detection. In: 2018 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO). IEEE, pp 762–774

25.

Gonçalves M, Condia JR, Reorda MS, Sterpone L, Azambuja J (2020) Improving GPU register file reliability with a comprehensive ISA extension. Microelectron Reliab 114:113768. https://doi.org/10.1016/j.microrel.2020.113768CrossRef

26.

Goncalves MM, Lamb IP, Rech P, Brum RM, Azambuja JR (2020) Improving selective fault tolerance in GPU register files by relaxing application accuracy. IEEE Trans Nucl Sci 67(7):1573–1580. https://doi.org/10.1109/TNS.2020.2982162CrossRef

27.

Gupta M, Lowell D, Kalamatianos J, Raasch S, Sridharan V, Tullsen D, Gupta R (2017) Compiler techniques to reduce the synchronization overhead of GPU redundant multithreading. In: 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC). IEEE, pp 1–6

28.

Sundaram A, Aakel A, Lockhart D, Thaker D, Franklin D (2008) Efficient fault tolerance in multi-media applications through selective instruction replication. In: Proceedings of the 2008 workshop on Radiation effects and fault tolerance in nanometer technologies, pp 339–346

29.

Kalra C, Previlon F, Rubin N, Kaeli D (2020) Armorall: compiler-based resilience targeting GPU applications. ACM Trans Archit Code Optim (TACO) 17(2):1–24CrossRef

30.

Goncalves M, Fernandes F, Lamb I, Rech P, Azambuja JR (2019) Selective fault tolerance for register files of graphics processing units. IEEE Trans Nucl Sci 66(7):1449–1456CrossRef

31.

dos Santos FF, Brandalero M, Basso PM, Hubner M, Carro L, Rech P (2020) Reduced-precision dwc for mixed-precision GPUs. In: 2020 IEEE 26th International Symposium on On-Line Testing and Robust System Design (IOLTS). IEEE, pp 1–6

32.

Andryc K, Merchant M, Tessier R (2013) Flexgrip: a soft GPGPU for FPGAs. In: 2013 International Conference on Field-Programmable Technology (FPT), pp 230–237. https://doi.org/10.1109/FPT.2013.6718358

33.

Lindholm E, Nickolls J, Oberman S, Montrym J (2008) Nvidia tesla: a unified graphics and computing architecture. IEEE Micro 28(2):39–55CrossRef

34.

Oh N, Shirvani PP, McCluskey EJ (2002) Error detection by duplicated instructions in super-scalar processors. IEEE Trans Reliab 51(1):63–75CrossRef

35.

Azambuja JR, Lapolli A, Rosa L, Kastensmidt FL (2011) Detecting sees in microprocessors through a non-intrusive hybrid technique. IEEE Trans Nucl Sci 58(3):993–1000CrossRef

36.

Mukherjee SS, Weaver C, Emer J, Reinhardt SK, Austin T (2003) A systematic methodology to compute the architectural vulnerability factors for a high-performance microprocessor. In: Proceedings. 36th Annual IEEE/ACM International Symposium on Microarchitecture, 2003. MICRO-36., pp 29–40. https://doi.org/10.1109/MICRO.2003.1253181

37.

Leveugle R, Calvez A, Maistri P, Vanhauwaert P (2009) Statistical fault injection: quantified error and confidence. In: 2009 Design, Automation and Test in Europe. IEEE, pp 502–506. https://doi.org/10.1109/DATE.2009.5090716

38.

Reis GA, Chang J, Vachharajani N, Mukherjee SS, Rangan R, August DI (2005) Design and evaluation of hybrid fault-detection systems. In: 32nd International Symposium on Computer Architecture (ISCA’05), pp 148–159. https://doi.org/10.1109/ISCA.2005.21

Titel: Evaluating low-level software-based hardening techniques for configurable GPU architectures
verfasst von: Marcio M. Goncalves
Josie E. Rodriguez Condia
Matteo Sonza Reorda
Luca Sterpone
Jose Rodrigo Azambuja
Publikationsdatum: 07.01.2022
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 6/2022
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-021-04154-z

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 6/2022

KS-DDoS: Kafka streams-based classification approach for DDoS attacks

Manipulating cyber army in pilot case forensics on social media

Resource pricing and offloading decisions in mobile edge computing based on the Stackelberg game

Clustering with a high-performance secure routing protocol for mobile ad hoc networks

LBTM: A lightweight blockchain-based trust management system for social internet of things

Attention-based framework for weakly supervised video anomaly detection

Premium Partner