Today's computational, experimental, and observational sciences rely on computations that
involve many related tasks. The success of a scientific mission often hinges on the computer …

We present a comprehensive survey on parallel I/O in the high-performance computing
(HPC) context. This is an important field for HPC because of the historic gap between …

Machine learning (ML) is being applied in a number of everyday contexts from image
recognition, to natural language processing, to autonomous vehicles, to product …

The prevalence of scientific workflows with high computational demands calls for their
execution on various distributed computing platforms, including large-scale leadership-class …

The FAIR principles of open science (Findable, Accessible, Interoperable, and Reusable)
have had transformative effects on modern large-scale computational science. In particular …

The benchmarks of I/O-intensive parallel applications are important for evaluating and
optimizing HPC softwares and hardwares. However, extracting high-fidelity benchmarks …

Large scale simulation performance is dependent on a number of components, however the
task of investigation and optimization has long favored computational and communication …

Computer scientists who work on tools and systems to support eScience (a variety of parallel
and distributed) applications usually use actual applications to prove that their systems will …

We present a serious game which we believe that has the potential to improve posture and
spinal health while still having fun. In our game, we correct postural deviations and perform …

One of the factors that limits the scale, performance, and sophistication of distributed
applications is the difficulty of concurrently executing them on multiple distributed computing …