Linking scientific instruments to exascale machines and analyzing the large volumes of data produced by the instruments requires workflow infrastructure that scales along many dimensions. In this white paper we generalize this problem to include control systems, analysis of data produced by supercomputers, computational steering and data assimilation. The requirements of distributed computing problems which couple HPC and streaming data, are distinct from those familiar from largescale parallel simulations, grid computing, data repositories and orchestration, which have generated sophisticated software platforms. Our analyses points to new research directions for a scalable infrastructure, to address this generalized streaming distributed ...
With the advancement in science and technology numerous complex scientific applications can be exec...
This tutorial will focus on providing attendees exposure to cutting-edge technologies for building r...
The ever-increasing volumes of scientific data com- bined with sophisticated techniques for extracti...
Modern scientific collaborations have opened up the op-portunity of solving complex problems that in...
Nowadays, HPC, Grid and Cloud systems are evolving very rapidly. However, the development of infrast...
Over the past four years, the Big Data and Exascale Computing (BDEC) project organized a series of f...
International audienceOver the past four years, the Big Data and Exascale Computing (BDEC) project o...
Large-scale data-intensive streaming applications in various science fields feature complex DAG-stru...
Modeling, coding and running large and multi-scale scientific applications require a high level abst...
Scientific exploration demands heavy usage of computational resources for large-scale and deep analy...
The processing power available to scientists and engineers using supercomputers over the last few de...
The advent of extreme-scale computing systems, e.g., Petaflop supercomputers, High Per-formance Comp...
Accurate digital twinning of the global challenges (GC) leads to computationally expensive coupled s...
We present a distributed framework that enables real-time streaming and visualization of data genera...
Accurate digital twinning of the global challenges (GC) leads to computationally expensive coupled s...
With the advancement in science and technology numerous complex scientific applications can be exec...
This tutorial will focus on providing attendees exposure to cutting-edge technologies for building r...
The ever-increasing volumes of scientific data com- bined with sophisticated techniques for extracti...
Modern scientific collaborations have opened up the op-portunity of solving complex problems that in...
Nowadays, HPC, Grid and Cloud systems are evolving very rapidly. However, the development of infrast...
Over the past four years, the Big Data and Exascale Computing (BDEC) project organized a series of f...
International audienceOver the past four years, the Big Data and Exascale Computing (BDEC) project o...
Large-scale data-intensive streaming applications in various science fields feature complex DAG-stru...
Modeling, coding and running large and multi-scale scientific applications require a high level abst...
Scientific exploration demands heavy usage of computational resources for large-scale and deep analy...
The processing power available to scientists and engineers using supercomputers over the last few de...
The advent of extreme-scale computing systems, e.g., Petaflop supercomputers, High Per-formance Comp...
Accurate digital twinning of the global challenges (GC) leads to computationally expensive coupled s...
We present a distributed framework that enables real-time streaming and visualization of data genera...
Accurate digital twinning of the global challenges (GC) leads to computationally expensive coupled s...
With the advancement in science and technology numerous complex scientific applications can be exec...
This tutorial will focus on providing attendees exposure to cutting-edge technologies for building r...
The ever-increasing volumes of scientific data com- bined with sophisticated techniques for extracti...