The International Exascale Software Project roadmap

By Jack J. Dongarra, P. Beckman, T. Moore, Patrick Aerts, G. Aloisio, Jean-Claude André, D. Barkai, J. Berthou, T. Boku, B. Braunschweig and 55 more. The international journal of high performance computing applications, 2011

769 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/a10b7a2c80e2bae49d46b980ed03c074fe36bb2a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Fan Yang
2. Andrew A. Chien
3. Pradip Bose
4. Subhasish G. Mitra
5. Sven Leyffer
6. Christian Engelmann
7. Jack J. Dongarra
8. George Bosilca

In Hardware and Architecture

1. Pradip Bose
2. Subhasish G. Mitra
3. Christian Engelmann
4. Jack J. Dongarra
5. George Bosilca
6. Franck Cappello

Citations in the corpus

• Addressing failures in exascale computing (2014, background): “The International Exascale Software Project Roadmap [39], which is the result of more than a year of coordinated effort by a large international group of experts, discusses various aspects of resilience.”
• ZCCloud: Exploring Wasted Green Power for High-Performance Computing (2016, background): “With power emerging as a critical obstacle for continue performance scaling [2], [36], power-efficiency has become a major objective of numerous research programs, including DARPA’s UHPC, OHPC, and PERFECT [37] programs which established goals of 75 Gigaflops/watt (system-level), the International E”
• Digital Twin: Values, Challenges and Enablers From a Modeling Perspective (2019, neutral): “ing exascale computing systems [457]–[459].”
• DAGuE: A Generic Distributed DAG Engine for High Performance Computing (2011, background): “DAGuE does not target heterogeneous ad hoc desktop grids, but supercomputers, whose architecture is envisioned [33] to be an homogeneous cluster of nodes with internal heterogeneity.”
• Exascale computing and big data (2015, methodology): “The associated roadmap for software development would take the community from its current position to exascale computing.(7)”