Efficiency of the Cyber 205 for Stochastic Simulations of a Simultaneous, Nonlinear, Dynamic Econometric Model

Author:

Ando Albert1,Beaumont Paul2,Ando Matthew3,Sims Christopher A.4

Affiliation:

1. UNIVERSITY OF PENNSYLVANIA PHILADELPHIA, PENNSYLVANIA 19104-6297

2. PURDUE UNIVERSITY WEST LAFAYETTE, INDIANA 47907

3. PRINCETON UNIVERSITY PRINCETON, NEW JERSEY 08540

4. SUBJECT AREA EDITOR

Abstract

A code for carrying out stochastic simulations of the MPS econometric model, a simultaneous, nonlinear, dynamic system of equations involving approximately 600 variables, was adapted to run on the CYBER 205 vector processor. The effi ciency gained relative to performance on an IBM 3081-GX was significant: the CPU time re quired for a given simulation was reduced by a factor of 10 to 12. However, this is considerably smaller than the theoretical gain expected from the manufacturer's ratings. The basic causes of this smaller gain are the fairly small real memory of the CYBER 205 and the inefficiency of the CYBER 205 vector processor in performing ele mentary function look-up. The primitive nature of the operating system and some aspects of the FORTRAN compiler on the CYBER 205 required more reprogramming of our large code than such a conversion should demand. However, potential gains from such a conversion will be great once the deficiencies described above are eliminated.

Publisher

SAGE Publications

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Chapter 7 Parallel computation;Handbook of Computational Economics;1996

2. Econometric Model Simulation On Parallel Computers;The International Journal of Supercomputing Applications;1993-09

3. VECTORIZATION AND ECONOMETRIC MODEL SIMULATION;Dynamic Modelling and Control of National Economies 1989;1990

4. Vectorization and Econometric Model Simulation;IFAC Proceedings Volumes;1989-06

5. High Performance Computing in Economics;Scientific Computing on Supercomputers;1989

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3