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Relevant bibliographies by topics / Reliable GPGPU application

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Journal articles
Dissertations / Theses
Conference papers

Academic literature on the topic 'Reliable GPGPU application'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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Journal articles on the topic "Reliable GPGPU application"

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Yang, Lishan, Bin Nie, Adwait Jog, and Evgenia Smirni. "SUGAR." Proceedings of the ACM on Measurement and Analysis of Computing Systems 5, no. 1 (2021): 1–29. http://dx.doi.org/10.1145/3447375.

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As Graphics Processing Units (GPUs) are becoming a de facto solution for accelerating a wide range of applications, their reliable operation is becoming increasingly important. One of the major challenges in the domain of GPU reliability is to accurately measure GPGPU application error resilience. This challenge stems from the fact that a typical GPGPU application spawns a huge number of threads and then utilizes a large amount of potentially unreliable compute and memory resources available on the GPUs. As the number of possible fault locations can be in the billions, evaluating every fault a

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Yang, Lishan, Bin Nie, Adwait Jog, and Evgenia Smirni. "SUGAR: Speeding Up GPGPU Application Resilience Estimation with Input Sizing." ACM SIGMETRICS Performance Evaluation Review 49, no. 1 (2022): 45–46. http://dx.doi.org/10.1145/3543516.3453917.

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As Graphics Processing Units (GPUs) are becoming a de facto solution for accelerating a wide range of applications, their reliable operation is becoming increasingly important. One of the major challenges in the domain of GPU reliability is to accurately measure GPGPU application error resilience. This challenge stems from the fact that a typical GPGPU application spawns a huge number of threads and then utilizes a large amount of potentially unreliable compute and memory resources available on the GPUs. As the number of possible fault locations can be in the billions, evaluating every fault a

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3

Bedkowski, Janusz Marian, and Timo Röhling. "Online 3D LIDAR Monte Carlo localization with GPU acceleration." Industrial Robot: An International Journal 44, no. 4 (2017): 442–56. http://dx.doi.org/10.1108/ir-11-2016-0309.

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Purpose This paper aims to focus on real-world mobile systems, and thus propose relevant contribution to the special issue on “Real-world mobile robot systems”. This work on 3D laser semantic mobile mapping and particle filter localization dedicated for robot patrolling urban sites is elaborated with a focus on parallel computing application for semantic mapping and particle filter localization. The real robotic application of patrolling urban sites is the goal; thus, it has been shown that crucial robotic components have reach high Technology Readiness Level (TRL). Design/methodology/approach

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Kaya, Ercument, and Isil Oz. "Compiler-Managed Replication of CUDA Kernels for Reliable Execution of GPGPU Applications." Journal of Circuits, Systems and Computers, March 13, 2024. http://dx.doi.org/10.1142/s0218126624502542.

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Dissertations / Theses on the topic "Reliable GPGPU application"

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SABENA, DAVIDE. "New Test and Fault Tolerance Techniques for Reliability Characterization of Parallel and Reconfigurable Processors." Doctoral thesis, Politecnico di Torino, 2015. http://hdl.handle.net/11583/2593389.

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Integrated electronic systems are more and more used in a wide number of applications and environments, ranging from mobile devices to safety-critical products. This wide distribution is mainly due to the miniaturization surrounded by an increasing computing power of semiconductor devices. However, there are many complex and arduous challenges associated to this phenomenon. One of these challenges is the reliability of electronic systems. Nowadays, several research e↵orts are aimed at improving the semiconductors reliability. Manufacturing processes, aging phenomena of components and environme

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Conference papers on the topic "Reliable GPGPU application"

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Mintu, Shafiul A., and David Molyneux. "Application of GPGPU to Accelerate CFD Simulation." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77649.

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Computational Fluid Dynamics (CFD) is widely used in industry and academic research to investigate complex fluid flow. The bottleneck of a realistic CFD simulation is its long simulation time. The simulation time is generally reduced by massively parallel Central Processing Unit (CPU) clusters, which are very expensive. In this paper, it is shown that the CFD simulation can be accelerated significantly by a novel hardware called General Purpose Computing on Graphical Processing Units (GPGPU). GPGPU is a cost-effective computing cluster, which uses the Compute Unified Device Architecture (CUDA)

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