In this paper we analyze the neutron sensitivity of GPU devices when executing a Fast Fourier Transform algorithm. The provided experimental results demonstrate that in the majority of cases the output is affected by multiple errors, caused by thread and data dependencies. ECC is experimentally proved not to be sufficient to provide high reliability. Experimental data and analytical studies are employed to design specific software-based hardening strategies, which are validated through fault-injection
We present an auto-tuning framework for FFTs on graphics pro-cessors (GPUs). Due to complex design o...
In this companion paper to “Algorithmic Choices in WARP – A Framework for Continuous Energy Monte Ca...
This work analyzes the performance of the reduced precision redundancy (RPR) error mitigation techni...
In this paper we analyze the neutron sensitivity of GPU devices when executing a Fast Fourier Transf...
In this paper we assess the neutron sensitivity of Graphics Processing Units (GPUs) when executing a...
In this paper, we compare the radiation response of GPUs executing matrix multiplication and FFT alg...
Thanks to the capability of efficiently executing massive computations in parallel, General Purpose ...
Abstract–Graphics Processing Units specifically designed for High Performance Computing applications...
International audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs expos...
The high processing power of GPUs makes them attractive for safety-critical applications, where tran...
Recently, General Purpose Graphic Processing Units (GPGPUs) have begun to be preferred to CPUs for s...
We investigate the sources of detected unrecoverable errors (DUEs) in graphics processing units (GPU...
This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - ...
International audienceThe reliability evaluation of Deep Neural Networks (DNNs) executed on Graphic ...
In this report we analyze the performance of the fast Fourier transform (FFT) on graphics hardware...
We present an auto-tuning framework for FFTs on graphics pro-cessors (GPUs). Due to complex design o...
In this companion paper to “Algorithmic Choices in WARP – A Framework for Continuous Energy Monte Ca...
This work analyzes the performance of the reduced precision redundancy (RPR) error mitigation techni...
In this paper we analyze the neutron sensitivity of GPU devices when executing a Fast Fourier Transf...
In this paper we assess the neutron sensitivity of Graphics Processing Units (GPUs) when executing a...
In this paper, we compare the radiation response of GPUs executing matrix multiplication and FFT alg...
Thanks to the capability of efficiently executing massive computations in parallel, General Purpose ...
Abstract–Graphics Processing Units specifically designed for High Performance Computing applications...
International audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs expos...
The high processing power of GPUs makes them attractive for safety-critical applications, where tran...
Recently, General Purpose Graphic Processing Units (GPGPUs) have begun to be preferred to CPUs for s...
We investigate the sources of detected unrecoverable errors (DUEs) in graphics processing units (GPU...
This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - ...
International audienceThe reliability evaluation of Deep Neural Networks (DNNs) executed on Graphic ...
In this report we analyze the performance of the fast Fourier transform (FFT) on graphics hardware...
We present an auto-tuning framework for FFTs on graphics pro-cessors (GPUs). Due to complex design o...
In this companion paper to “Algorithmic Choices in WARP – A Framework for Continuous Energy Monte Ca...
This work analyzes the performance of the reduced precision redundancy (RPR) error mitigation techni...