If we hope to automatically detect and diagnose failures in large-scale computer systems,
we must study real deployed systems and the data they generate. Progress has been …

This paper provides an analysis of failures and their impact for Blue Waters, the Cray hybrid
(CPU/GPU) supercomputer at the University of Illinois at Urbana-Champaign. The analysis …

Resilience is one of the key challenges in maintaining high efficiency of future extreme scale
supercomputers. Researchers and system practitioners rely on field-data studies to …

The growing computational and storage needs of several scientific applications mandate the
deployment of extreme-scale parallel machines, such as IBM's BlueGene/L which can …

Hardware failures have a big impact on the dependability of large-scale data centers. We
present studies on over 290,000 hardware failure reports collected over the past four years …

Increase in graphics hardware performance and improvements in programmability has
enabled GPUs to evolve from a graphics-specific accelerator to a general-purpose …

In large-scale networked computing systems, component failures become norms instead of
exceptions. Failure prediction is a crucial technique for self-managing resource burdens …

Distributed systems have been widely used in many safety‐critical areas. Any abnormalities
(eg, service interruption or service quality degradation) could lead to application crashes or …

Parallelism provided by the GPU architecture has enabled domain scientists to simulate
physical phenomena at a much faster rate and finer granularity than what was previously …

The high computational capability of graphics processing units (GPUs) is enabling and
driving the scientific discovery process at large-scale. The world's second fastest …