Torus networks are an attractive topology in supercomputing, balancing the tradeoff
between network diameter and hardware costs. The nodes in a torus network are connected …

We present P5, a web-based visualization toolkit that combines declarative visualization
grammar and GPU computing for progressive data analysis and visualization. To …

The overall efficiency of an extreme-scale supercomputer largely relies on the performance
of its network interconnects. Several of the state of the art supercomputers use networks …

Dragonfly is a highly scalable, low-diameter, and cost-efficient network topology, which has
been adopted in new exascale High Performance Computing (HPC) systems. However …

We present P4, an information visualization toolkit that combines declarative design
specification and GPU computing for building high-performance interactive systems. Most of …

Historically, scientific computing efforts have demonstrated the clear need for, and effective
use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are …

Understanding and tuning the performance of extreme-scale parallel computing systems
demands a streaming approach due to the computational cost of applying offline algorithms …

The Message Passing Interface (MPI) is the most prominent and dominant programming
model for scientific computing in super-computing systems today. Although many general …

The ability to monitor and interpret hardware system events and behaviors is crucial to
improving the robustness and reliability of these systems, especially in a supercomputing …

To optimize the performance and efficiency of HPC applications, programmers and analysts
often need to collect various performance metrics for each computer at different time points …