PACS-CS: a large-scale bandwidth-aware PC cluster for scientific computation

2006 ◽  
Author(s):  
T. Boku ◽  
M. Sato ◽  
A. Ukawa ◽  
D. Takahashi ◽  
S. Sumimoto ◽  
...  
Keyword(s):  
Large Scale ◽  
Scientific Computation ◽  
Pc Cluster

Large-scale Parallel FE Analysis by PC-cluster Using GeoFEM

2000 ◽  
Vol 2000.13 (0) ◽  
pp. 489-490
Author(s):  
Hiroshi OKUDA ◽  
Masaki NAGATA ◽  
Kazuteru GARATANI
Keyword(s):  
Large Scale ◽  
Fe Analysis ◽  
Pc Cluster

Large Scale Scientific Computation.

1986 ◽  
Vol 46 (174) ◽  
pp. 766
Author(s):  
L. B. W. ◽  
Seymour V. Parter
Keyword(s):  
Large Scale ◽  
Scientific Computation

scholarly journals Compiler Technology for Parallel Scientific Computation

1994 ◽  
Vol 3 (3) ◽  
pp. 201-225 ◽  
Author(s):  
Can Özturan ◽  
Balaram Sinharoy ◽  
Boleslaw K. Szymanski
Keyword(s):  
Parallel Computation ◽  
Programming Language ◽  
Code Generation ◽  
Large Scale ◽  
User Involvement ◽  
Scientific Computation ◽  
Data Alignment ◽  
Source Program ◽  
Parallel Code ◽  
Run Time

There is a need for compiler technology that, given the source program, will generate efficient parallel codes for different architectures with minimal user involvement. Parallel computation is becoming indispensable in solving large-scale problems in science and engineering. Yet, the use of parallel computation is limited by the high costs of developing the needed software. To overcome this difficulty we advocate a comprehensive approach to the development of scalable architecture-independent software for scientific computation based on our experience with equational programming language (EPL). Our approach is based on a program decomposition, parallel code synthesis, and run-time support for parallel scientific computation. The program decomposition is guided by the source program annotations provided by the user. The synthesis of parallel code is based on configurations that describe the overall computation as a set of interacting components. Run-time support is provided by the compiler-generated code that redistributes computation and data during object program execution. The generated parallel code is optimized using techniques of data alignment, operator placement, wavefront determination, and memory optimization. In this article we discuss annotations, configurations, parallel code generation, and run-time support suitable for parallel programs written in the functional parallel programming language EPL and in Fortran.

Large scale scientific computation via minicomputer

1977 ◽  
Vol 1 (2) ◽  
pp. 85-90 ◽  
Author(s):  
Henry F. Schaefer ◽  
William H. Miller
Keyword(s):  
Large Scale ◽  
Scientific Computation
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