High-performance computing (HPC) is recognized as one of the pillars for further progress in
science, industry, medicine, and education. Current HPC systems are being developed to …

Performance analysis tools are essential in the process of understanding application
behavior, identifying critical performance issues and adapting applications to new …

Many engineering applications require complex frameworks to simulate the intricate and
extensive sub-problems involved. However, performance analysis tools can struggle when …

This paper proposes OMP-WhIP, a profiler that measures inherent parallelism in the
program for a given input and provides what-if analyses to estimate improvements in …

Cloud computing adds great on-demand scalability to stream processing systems with its
pay-per-use cost model. However, to promise service level agreements to users while …

Abstract Model factors provide initial insight into fundamental issues of parallel applications.
These metrics elaborate beyond conventional HPC metrics to indicate whether an …

The last few years saw the emergence of 64-bit ARM SoCs targeted for mobile systems and
servers. Mobile-class SoCs rely on the heterogeneous integration of a mix of CPU cores …

In this paper, we address the decreasing performance of the FFTXlib, the Fast Fourier
Transformation (FFT) kernel of Quantum ESPRESSO, when scaling to a full KNL node. An …

Many HPC and modern Big Data processing applications belong to a class of so-called
scale-out applications, where the application dataset is partitioned and processed by a …

Geoscientific modeling is constantly evolving, with next-generation geoscientific models and
applications placing large demands on high-performance computing (HPC) resources …