… Finally, we identify the promising paths to meet the reliability levels of … Spatial support
vector regression to detect silent errors in the exascale era. In Proceedings of the 16th IEEE/ACM …

… that exascale systems will experience faults and errors more fre… However, silent data corruption
(SDC) might require more … a global memory address space partitioned across the nodes. …

… are designed/utilized towards exascale computing, inevitably … on one-day period (27-March-2017)
due to space limit and … using partial labels based on PU learning and Support Vector …

… silent data corruption detectors by leveraging support vector … The right replication level to
detect and correct silent errors at … their spatial locality and providing the mean relative error (…

… scientists with expertise in exascale computing to discuss novel … for detection, containment
and mitigation of silent data … -resolution in space or time and the error estimators themselves …

… , silent data corruption (SDC) errors, or simply silent errors (… the detection interval required
to detect the error in the error … with their spatial locality and provide the mean relative error (…

… , we have to assume that exascale machines will fail frequently … from the other over a longer
period, it is reasonable to … follow-up space-time predictors to which our error detection and …

… ing pixels in order to pick out spatially close parts of features. … investment and involves
human error. Automated methods … used supervised classifiers include support vector machines, …

… latter one which is soft error or silent data corruption (SDC). … characteristics in both time and
space dimension. For the soft … , aims to develop MD simulation at exascale to address the key …

… the complicated spatial and temporal correlation between error … that affects computation for
only a short period of time, … roll back for recovering once an error is detected). However, most …