radix
radix 

所属分类:Linux/Unix编程
开发工具:C/C++
文件大小:37KB
下载次数:4
上传日期:2009-09-05 21:40:25
上 传 者derek.shepred
说明:  实现了在多处理器上可运行的矩阵相乘的程序
(Achieved in a multi-processor run of the matrix multiplication program)

文件列表:
radix\makefile (520, 2006-03-17)
radix\RADIX (40156, 2008-12-03)
radix\radix.c (25729, 2008-11-28)
radix\radix.o (31340, 2008-12-03)
radix (0, 2008-12-03)

GENERAL INFORMATION: The RADIX program implements an integer radix sort based on the method described in: Blelloch, G. E., et. al. A Comparison of Sorting Algorithms for the Connection Machine CM-2. In Symposium on Parallel Algorithms and Architectures, pp. 3-16, July 1991. A description of this implementation can be found in: Woo, S. C., Singh, J. P., and Hennessy, J. L. The Performance Advantages of Integrating Message Passing in Cache-Coherent Multiprocessors. Technical Report CSL-TR-93-593, Stanford University, December 1993. This program works under both the Unix FORK and SPROC models. RUNNING THE PROGRAM: To see how to run the program, please see the comment at the top of the file radix.C, or run the application with the "-h" command line option. Four command line parameters can be specified, of which the ones which would normally be changed are the number of keys to sort, the radix for sorting, and the number of processors. The radix used for sorting must be a power of 2. Optional command line parameters allow timing information to be printed out at the end of the program, testing to make sure all keys are sorted correctly, and keys to be printed out in sorted order. BASE PROBLEM SIZE: The base problem size for an upto-*** processor machine is 256k (262,144) keys to be sorted and a radix of 1024. The default values should be used for other parameters (except the number of processors, which can be varied). For larger problems, the number of keys can also be increased by factors of 2. Any changes to these parameters should be reported when results are presented. DATA DISTRIBUTION: Our "POSSIBLE ENHANCEMENT" comments in the source code tell where one might want to distribute data and how. Data distribution has an impact on performance on the Stanford DASH multiprocessor.

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