COMPARISON OF GPU AND CPU EFFICIENCY WHILE SOLVING HEAT CONDUCTION PROBLEMS

Overview of GPU usage while solving different engineering problems, comparison between CPU and GPU computations and overview of the heat conduction problem are provided in this paper. The Jacobi iterative algorithm was implemented by using Python, TensorFlow GPU library and NVIDIA CUDA technology. Numerical experiments were conducted with 6 CPUs and 4 GPUs. The fastest used GPU completed the calculations 19 times faster than the slowest CPU. On average, GPU was from 9 to 11 times faster than CPU. Significant relative speed-up in GPU calculations starts when the matrix contains at least 4002 floating-point numbers.

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NUMERICAL SOLUTION OF HYPERBOLIC HEAT CONDUCTION EQUATION

Mathematical Modelling and Analysis ◽

10.3846/1392-6292.2009.14.11-24 ◽

2009 ◽

Vol 14 (1) ◽

pp. 11-24 ◽

Cited By ~ 17

Author(s):

Raimondas Čiegis

Keyword(s):

Heat Conduction ◽

Heat Conduction Equation ◽

Numerical Experiments ◽

Heat Conduction Problem ◽

Hyperbolic Heat Conduction ◽

Euler Scheme ◽

Unconditionally Stable ◽

Implicit Euler Scheme ◽

Numerical Viscosity ◽

Numerical Oscillations

Hyperbolic heat conduction problem is solved numerically. The explicit and implicit Euler schemes are constructed and investigated. It is shown that the implicit Euler scheme can be used to solve efficiently parabolic and hyperbolic heat conduction problems. This scheme is unconditionally stable for both problems. For many integration methods strong numerical oscillations are present, when the initial and boundary conditions are discontinuous for the hyperbolic problem. In order to regularize the implicit Euler scheme, a simple linear relation between time and space steps is proposed, which automatically introduces sufficient amount of numerical viscosity. Results of numerical experiments are presented.

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EVALUATION OF THE HYPER‐THREADING TECHNOLOGY FOR HEAT CONDUCTION‐TYPE PROBLEMS

Mathematical Modelling and Analysis ◽

10.3846/1392-6292.2007.12.459-468 ◽

2007 ◽

Vol 12 (4) ◽

pp. 459-468

Author(s):

Sergėjus Ivanikovas ◽

Gintautas Dzemyda

Keyword(s):

Heat Conduction ◽

System Performance ◽

Heat Conduction Problem ◽

Standard Heat ◽

Conduction Type ◽

Speed Up ◽

Dual Core ◽

With Memory ◽

Main Factor

Symmetric Multi Processor (SMP) systems become popular and available for most users nowadays. The main factor that affects the performance while working with a large amount of data with the SMP system is operating memory speed. Hyper‐Threading technology lets to increase the amount of threads working in parallel and to speed‐up the execution of program using the same hardware. A standard heat conduction problem was chosen as a benchmark to test the SMP system performance while working with memory‐intensive tasks. The results of practical tests and the quantitative estimations of efficiency are presented in the article. The experiments indicate how Hyper‐Threading technology helps to use the SMP systems and dual-core processor systems more effectively while working with a large amount of data.

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