Kerrighed:: A single system image cluster operating system for high performance computing

被引:0
作者
Morin, C [1 ]
Lottiaux, R
Vallée, G
Gallard, P
Utard, G
Badrinath, R
Rilling, L
机构
[1] INRIA, IRISA, Paris Project Team, Paris, France
[2] Indian Inst Technol, Kharagpur 721302, W Bengal, India
[3] ENS Cachan, Antenna Bretagne, Cachan, France
来源
EURO-PAR 2003 PARALLEL PROCESSING, PROCEEDINGS | 2003年 / 2790卷
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Kerrighed is a single system image operating system for clusters. Kerrighed aims at combining high performance, high availability and ease of use and programming. Kerrighed implements a set of global resource management services that aim at making resource distribution transparent to the applications, at managing resource sharing in and between applications and at taking benefit of the whole cluster resources for demanding applications. Kerrighed is implemented as a set of modules extending the Linux kernel. Legacy multi-threaded applications and message-passing based applications developed for an SNIP PC running Linux can be executed without re-compilation on a Kerrighed cluster. The proposed demonstration presents a prototype of Kerrighed running on a cluster of four portable PCs. It shows the main features of Kerrighed in global memory, process and stream management by running multi-threaded and MPI applications on top of Kerrighed.
引用
收藏
页码:1291 / 1294
页数:4
相关论文
共 50 条
[31]   Design of laser image recognition system based on high performance computing of spatiotemporal data [J].
Wu, Zongfu ;
Hou, Fazhong .
INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2024, 18 (04) :2701-2714
[32]   Triolet: A Programming System that Unifies Algorithmic Skeleton Interfaces for High-Performance Cluster Computing [J].
Rodrigues, Christopher ;
Jablin, Thomas ;
Dakkak, Abdul ;
Hwu, Wen-Mei .
ACM SIGPLAN NOTICES, 2014, 49 (08) :247-258
[33]   A high-performance content-based image retrieval system on PC cluster [J].
Jeng, WM ;
Hsiao, JH .
6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XI, PROCEEDINGS: COMPUTER SCIENCE II, 2002, :525-530
[34]   High performance computing in multibody system design [J].
Baldini, S ;
Giraud, L ;
Izaguirre, JG ;
Jimenez, JM ;
Matey, LM .
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 1999, 13 (02) :99-106
[35]   High performance computing in power system applications [J].
Falcao, DM .
VECTOR AND PARALLEL PROCESSING - VECPAR'96, 1997, 1215 :1-23
[36]   Hierarchical Visualization System for High Performance Computing [J].
Dzhosan, Oxana ;
Popova, Nina ;
Korzh, Anton .
PARALLEL COMPUTING: FROM MULTICORES AND GPU'S TO PETASCALE, 2010, 19 :177-184
[37]   The analysis of the operating performance of a chiller system based on hierarchal cluster method [J].
Li, Manfeng ;
Ju, Yonglin .
ENERGY AND BUILDINGS, 2017, 138 :695-703
[38]   In-kernel integration of operating system and infiniband functions for high performance computing clusters: A DSM example [J].
Liss, L ;
Birk, Y ;
Schuster, A .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2005, 16 (09) :830-840
[39]   Ensuring system performance for cluster and single server systems [J].
Avritzer, Alberto ;
Bondi, Andre ;
Weyuker, Elaine J. .
JOURNAL OF SYSTEMS AND SOFTWARE, 2007, 80 (04) :441-454
[40]   OPERATING SYSTEM CONDISERATIONS FOR STATISTICAL COMPUTING [J].
GODFREY, MD .
THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 1971, 20 (01) :45-&