GPU-Qin: A methodology for evaluating the error resilience of GPGPU applications

@article{Fang2014GPUQinAM,
  title={GPU-Qin: A methodology for evaluating the error resilience of GPGPU applications},
  author={Bo Fang and Karthik Pattabiraman and Matei Ripeanu and Sudhanva Gurumurthi},
  journal={2014 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)},
  year={2014},
  pages={221-230}
}
While graphics processing units (GPUs) have gained wide adoption as accelerators for general-purpose applications (GPGPU), the end-to-end reliability implications of their use have not been quantified. Fault injection is a widely used method for evaluating the reliability of applications. However, building a fault injector for GPGPU applications is challenging due to their massive parallelism, which makes it difficult to achieve representativeness while being time-efficient. This paper makes… CONTINUE READING
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