Improving GPU Reliability with Software-Managed Pipeline Parity for Error Detection and Correction
Author:
Affiliation:
1. Federal University of Rio Grande do Sul (UFRGS),Institute of Informatics - PPGC - PGMICRO
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10506108/10506116/10538027.pdf?arnumber=10538027
Reference23 articles.
1. Arithmetic-intensity-guided fault tolerance for neural network inference on GPUs
2. Accelerating schedule space exploration of multi-threaded programs with GPUs
3. Fault-Tolerant Systolic Array Based Accelerators for Deep Neural Network Execution
4. Design Space Exploration of Embedded Applications on Heterogeneous CPU-GPU Platforms
5. Analyzing and Increasing the Reliability of Convolutional Neural Networks on GPUs
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