Computing machine for Fourier's synthesis

In recent years, cloud workflow task scheduling has always been an important research topic in the business world. Cloud workflow task scheduling means that the workflow tasks submitted by users are allocated to appropriate computing resources for execution, and the corresponding fees are paid in real time according to the usage of resources. For most ordinary users, they are mainly concerned with the two service quality indicators of workflow task completion time and execution cost. Therefore, how cloud service providers design a scheduling algorithm to optimize task completion time and cost is a very important issue. This paper proposes research on workflow scheduling based on mobile cloud computing machine learning, and this paper conducts research by using literature research methods, experimental analysis methods, and other methods. This article has deeply studied mobile cloud computing, machine learning, task scheduling, and other related theories, and a workflow task scheduling system model was established based on mobile cloud computing machine learning from different algorithms used in processing task completion time, task service costs, task scheduling, and resource usage The situation and the influence of different tasks on the experimental results are analyzed in many aspects. The algorithm in this paper speeds up the scheduling time by about 7% under a different number of tasks and reduces the scheduling cost by about 2% compared with other algorithms. The algorithm in this paper has been obviously optimized in time scheduling and task scheduling.

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The Eniac, an Electronic Computing Machine

Nature ◽

10.1038/158500a0 ◽

1946 ◽

Vol 158 (4015) ◽

pp. 500-506 ◽

Cited By ~ 33

Author(s):

D. R. HARTREE

Keyword(s):

Computing Machine ◽

Electronic Computing

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A scaleable FIR filter using 32-bit floating-point complex arithmetic on a configurable computing machine

Proceedings. IEEE Symposium on FPGAs for Custom Computing Machines (Cat. No.98TB100251) ◽

10.1109/fpga.1998.707941 ◽

2002 ◽

Cited By ~ 2

Author(s):

A. Walters ◽

P. Athanas

Keyword(s):

Fir Filter ◽

Floating Point ◽

Configurable Computing ◽

Complex Arithmetic ◽

Computing Machine

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Volumetric visualization algorithm development for an FPGA-based custom computing machine

10.1117/12.309554 ◽

1998 ◽

Author(s):

Sami J. Sallinen ◽

Jyrki Alakuijala ◽

Hannu Helminen ◽

Joakim Laitinen

Keyword(s):

Algorithm Development ◽

Computing Machine

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An Improved Method for Calculating Free Vibrations in Systems of Several Degrees of Freedom

Journal of Applied Mechanics ◽

10.1115/1.4008849 ◽

1938 ◽

Vol 5 (2) ◽

pp. A61-A66

Author(s):

Winston M. Dudley

Keyword(s):

Degrees Of Freedom ◽

Numerical Solutions ◽

Matrix Theory ◽

Free Vibrations ◽

Initial Disturbance ◽

Improved Method ◽

Matrix Methods ◽

Computing Machine ◽

The Matrix ◽

Time Required

Abstract In 1934 two English investigators (1) published a method for calculating the various modes and frequencies of vibration of a system having several degrees of freedom. Their method, which is based on matrices, greatly shortens the time spent in obtaining numerical solutions in many important problems, notably those with immovable foundations. In this paper is presented a new theorem which (a) makes possible a further reduction of nearly one half in the time required, so that solutions up to 20 deg or more of freedom are now practical and (b) makes it then possible to determine the motion of the system after any initial disturbance in a few minutes, instead of several hours as required by older methods. It is useful in the latter respect whether the modes have been determined by matrix methods, or not. Although the paper gives simpler proofs than any previously published, knowledge of the matrix theory is not required in using the method. Problems are analyzed by a tabular process, in which an ordinary computing machine helps greatly. Comments based on computing experience are given. A simple numerical example has been given elsewhere (1).

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