In this paper, we compare the radiation response of GPUs executing matrix multiplication and FFT algorithms. The provided experimental results demonstrate that for both algorithms, in the majority of cases, the output is affected by multiple errors. The architectural and code analysis highlight that multiple errors are caused by shared resources corruption or thread dependencies. The experimental data and analytical studies can be fruitfully employed to evaluate the expected error rate of GPUs in realistic applications and to design specific and optimized software-based hardening procedures
This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - ...
A standardized test method has been created to characterize and stress graphics processing units (GP...
International audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs expos...
In this paper we assess the neutron sensitivity of Graphics Processing Units (GPUs) when executing a...
In this paper we analyze the neutron sensitivity of GPU devices when executing a Fast Fourier Transf...
Abstract–Graphics Processing Units specifically designed for High Performance Computing applications...
We investigate the sources of detected unrecoverable errors (DUEs) in graphics processing units (GPU...
Thanks to the capability of efficiently executing massive computations in parallel, General Purpose ...
Recently, General Purpose Graphic Processing Units (GPGPUs) have begun to be preferred to CPUs for s...
The high processing power of GPUs makes them attractive for safety-critical applications, where tran...
International audienceAn algorithm level technique to harden matrix multiplication is described and ...
In this paper, we evaluate the error criticality of radiation-induced errors on modern High-Performa...
Deep learning technology has enabled the development of increasingly complex safety-related autonomo...
In this report we analyze the performance of the fast Fourier transform (FFT) on graphics hardware...
In this companion paper to “Algorithmic Choices in WARP – A Framework for Continuous Energy Monte Ca...
This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - ...
A standardized test method has been created to characterize and stress graphics processing units (GP...
International audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs expos...
In this paper we assess the neutron sensitivity of Graphics Processing Units (GPUs) when executing a...
In this paper we analyze the neutron sensitivity of GPU devices when executing a Fast Fourier Transf...
Abstract–Graphics Processing Units specifically designed for High Performance Computing applications...
We investigate the sources of detected unrecoverable errors (DUEs) in graphics processing units (GPU...
Thanks to the capability of efficiently executing massive computations in parallel, General Purpose ...
Recently, General Purpose Graphic Processing Units (GPGPUs) have begun to be preferred to CPUs for s...
The high processing power of GPUs makes them attractive for safety-critical applications, where tran...
International audienceAn algorithm level technique to harden matrix multiplication is described and ...
In this paper, we evaluate the error criticality of radiation-induced errors on modern High-Performa...
Deep learning technology has enabled the development of increasingly complex safety-related autonomo...
In this report we analyze the performance of the fast Fourier transform (FFT) on graphics hardware...
In this companion paper to “Algorithmic Choices in WARP – A Framework for Continuous Energy Monte Ca...
This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - ...
A standardized test method has been created to characterize and stress graphics processing units (GP...
International audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs expos...