Scientific Machine Learning (SciML) and Artificial Intelligence (AI) will have broad use and
transformative effects across the Department of Energy. Accordingly, the January 2018 Basic …

Big data analytics provides an interdisciplinary framework that is essential to support the
current trend for solving real‐world problems collaboratively. The progression of big data …

This work is based on the seminar titled 'Resiliency in Numerical Algorithm Design for
Extreme Scale Simulations' held March 1–6, 2020, at Schloss Dagstuhl, that was attended …

Soft errors caused by transient bit flips have the potential to significantly impact an
application's behavior. This has motivated the design of an array of techniques to detect …

Data reduction techniques have been widely demanded and used by large-scale high
performance computing (HPC) applications because of vast volumes of data to be produced …

With the decreasing size and voltage level of internal device components, soft errors are
increasing and constitute a major threat on electronic devices. Silent data corruption (SDC) …

Understanding the impact of soft errors on applications can be expensive. Often, it requires
an extensive error injection campaign involving numerous runs of the full application in the …

Nowadays, high-performance computing (HPC) is stepping forward to exascale era.
However, silent data corruption (SDC) behaved as bit-flipping can cause disastrous …

We present FPDetect, a low-overhead approach for detecting logical errors and soft errors
affecting stencil computations without generating false positives. We develop an offline …

This book describes the benefits and drawbacks inherent in the use of virtual platforms (VPs)
to perform fast and early soft error assessment of multicore systems. The authors show that …