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Covering research topics from system software such as programming languages, compilers, runtime systems, operating systems, communication middleware, and large-scale file systems, as well as application development support software and big-data processing software, this book presents cutting-edge software technologies for extreme scale computing. The findings presented here will provide researchers in these fields with important insights for the further development of exascale computing technologies.This book grew out of the post-peta CREST research project funded by the Japan Science and Technology Agency, the goal of which was to establish software technologies for exploring extreme performance computing beyond petascale computing. The respective were contributed by 14 research teams involved in the project.
In addition to advanced technologies for large-scale numerical computation, the project addressed the technologies required for big data and graph processing, the complexity of memory hierarchy, and the power problem. Mapping the direction of future high-performance computing was also a central priority.
Table des matières
JST CREST Post-petascale software project bridging to exascale computing.- ppOpen-HPC/pK-Open-HPC: Application Development Framework with Automatic Tuning (AT).- Scalable Eigen-analysis Engine for Large-scale Eigenvalue Problems.- System Software for Many-core & Multi-core Architecture.- Highly Productive, High Performance Application Frameworks for Post Petascale Computing.- System Software for Data-intensive Science.- Approaches for Memory-Efficient Communication Library and Runtime Communication Optimization.- A development platform for embedded domain-specific languages.- Xevolver: a user-defined code transformation approach to streamlining legacy code migration.- Numerical Library Based on Hierarchical Domain Decomposition.- Advanced Computing & Optimization Infrastructure for Extremely Large-Scale Graphs on Post Peta-Scale Supercomputers.- Software Technology that Deals with Deeper Memory Hierarchy in Post-petascale Era.- Power Management Framework for Post-Petascale Supercomputers.- Project CASSIA -Framework for Exhaustive and Large-scale Social Simulation-.- GPU Accelerated Language and Communication Support by FPGA.
A propos de l'auteur
Mitsuhisa Sato is a deputy director of the RIKEN Center for Computational Science (R-CCS). He was a professor at the Graduate School of Systems and Information Engineering, University of Tsukuba from 2001. He has been working as a director of the Center for Computational Sciences, University of Tsukuba from 2007 to 2013. Since October 2010, he is appointed to the research team leader of programming environment research team in the Advanced Institute of Computational Science (AICS), former R-CCS, which was the organization to run Japanese petaflops facility "K computer". Since 2014, he is working as a team leader of architecture development team in the Japanese FLAGSHIP2020 project to develop the next system of the K computer in R-CCS. He is a professor (Cooperative Graduate School Program) and professor emeritus of University of Tsukuba.
Résumé
Covering research topics from system software such as programming languages, compilers, runtime systems, operating systems, communication middleware, and large-scale file systems, as well as application development support software and big-data processing software, this book presents cutting-edge software technologies for extreme scale computing. The findings presented here will provide researchers in these fields with important insights for the further development of exascale computing technologies.This book grew out of the post-peta CREST research project funded by the Japan Science and Technology Agency, the goal of which was to establish software technologies for exploring extreme performance computing beyond petascale computing. The respective were contributed by 14 research teams involved in the project.
In addition to advanced technologies for large-scale numerical computation, the project addressed the technologies required for big data and graph processing, the complexity of memory hierarchy, and the power problem. Mapping the direction of future high-performance computing was also a central priority.
