10 citations · 10 across the 5 of their papers we have counts for
7 papers
MOARD: Modeling Application Resilience to Transient Faults on Data Objects
Luanzheng Guo, Dong Li
Understanding application resilience (or error tolerance) in the presence of hardware transient faults on data objects is critical to ensure computing integrity and enable efficien…
Reinit++: Evaluating the Performance of Global-Restart Recovery Methods For MPI Fault Tolerance
Giorgis Georgakoudis, Luanzheng Guo, Ignacio Laguna
Scaling supercomputers comes with an increase in failure rates due to the increasing number of hardware components. In standard practice, applications are made resilient through ch…
MATCH: An MPI Fault Tolerance Benchmark Suite
Luanzheng Guo, Giorgis Georgakoudis, Konstantinos Parasyris +2
MPI has been ubiquitously deployed in flagship HPC systems aiming to accelerate distributed scientific applications running on tens of hundreds of processes and compute nodes. Main…
A High-Performance Sparse Tensor Algebra Compiler in Multi-Level IR
Ruiqin Tian, Luanzheng Guo, Jiajia Li +2
Tensor algebra is widely used in many applications, such as scientific computing, machine learning, and data analytics. The tensors represented real-world data are usually large an…
A Preliminary Study of Neural Network-based Approximation for HPC Applications
Wenqian Dong, Anzheng Guolu, Dong Li
Machine learning, as a tool to learn and model complicated (non)linear relationships between input and output data sets, has shown preliminary success in some HPC problems. Using m…
PARIS: Predicting Application Resilience Using Machine Learning
Luanzheng Guo, Dong Li, Ignacio Laguna
Extreme-scale scientific applications can be more vulnerable to soft errors (transient faults) as high-performance computing systems increase in scale. The common practice to evalu…