Duration automation in scheduling program for a cluster computer system

Context. High-performance computing systems are needed to solve many scientific problems and to work with complex applied problems. Previously, real parallel data processing was supported only by supercomputers, which are very limited and difficult to access. Currently, one way to solve this problem is to build small, cheap clusters based on single-board computers Raspberry Pi. Objective. The goal of the work is the creation of a complex criterion for the efficiency of the cluster system, which could properly characterize the operation of such a system and find the dependences of the performance of the cluster system based on Raspberry Pi 3B+ on the number of boards in it with different cooling systems. Method. It is offered to apply in the analysis of small cluster computer systems the complex criterion of efficiency of work of cluster system which will consider the general productivity of cluster computer system, productivity of one computing element in cluster computer system, electricity consumption by cluster system, electricity consumption per one computing element, the cost of calculating 1 Gflops cluster computer system, the total cost of the cluster computer system. Results. The developed complex criterion of cluster system efficiency was used to create an experimental cluster system based on single-board computers Raspberry Pi 3B+. Mathematical models of the dependence of the performance of a small cluster system based on single-board computers Raspberry Pi 3B+ depending on the number of boards in it with different cooling systems have also been developed. Conclusions. The conducted experiments confirmed the expediency of using the developed complex criterion of efficiency of the cluster system and allow to recommend it for use in practice when creating small cluster systems. Prospects for further research are to determine the weights of the constituent elements of the complex criterion of efficiency of the cluster system, as well as in the experimental study of the proposed weights.

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A cluster computer system for the analysis and classification of massively large biomedical image data

Computers in Biology and Medicine ◽

10.1016/s0010-4825(97)00032-2 ◽

1998 ◽

Vol 28 (1) ◽

pp. 47-60 ◽

Cited By ~ 6

Author(s):

T Daggett ◽

I.R Greenshields

Keyword(s):

Computer System ◽

Image Data ◽

Biomedical Image ◽

Cluster Computer

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Some Recent Results in Quiescent Prominence Spectrometry

International Astronomical Union Colloquium ◽

10.1017/s0252921100065179 ◽

1979 ◽

Vol 44 ◽

pp. 41-47

Author(s):

Donald A. Landman

Keyword(s):

Real Time ◽

Computer System ◽

Spectral Response ◽

Absolute Intensity ◽

Solar Observatory ◽

Target Size ◽

Small Target ◽

Signal Averaging ◽

Quiescent Prominence

This paper describes some recent results of our quiescent prominence spectrometry program at the Mees Solar Observatory on Haleakala. The observations were made with the 25 cm coronagraph/coudé spectrograph system using a silicon vidicon detector. This detector consists of 500 contiguous channels covering approximately 6 or 80 Å, depending on the grating used. The instrument is interfaced to the Observatory’s PDP 11/45 computer system, and has the important advantages of wide spectral response, linearity and signal-averaging with real-time display. Its principal drawback is the relatively small target size. For the present work, the aperture was about 3″ × 5″. Absolute intensity calibrations were made by measuring quiet regions near sun center.

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