In this article, we compare the support for SIMD instructions for Julia and Fortran. The comparison is carried out according to the methodology described in work of T. Kalibera, R. E. Jones. The first part of the article gives a brief description of this technique. We emphasize on the practical implementation using Python, NumPy and SciPy. The second part of the article briefly discusses the syntactic capabilities of Fortran and Julia to work with SIMD processor extensions. Specific code snippets are given. Next, the performance of Julia and Fortran is compared for arithmetic operations on arrays of small length. The results are presented in tabular and graphical form. © 2019 Published under licence by IOP Publishing Ltd
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peer reviewedThis article presents the implementation of the material point method (MPM) using Julia...
This article describes how to develop a software test-bed to simulate the excution of instructions o...
This work describes dynamic programming language Julia. Firstly, user is introduced to syntax and im...
The state of numerical computing is currently characterized by a divide between highly efficient yet...
The Julia programming language is gaining enormous popularity. Julia was designed to be easy and fas...
Julia's potential for solving complex astrodynamics problems is studied. Julia is a high-level, new,...
We argue that the Julia programming language is a compelling alternative to implementations in Pytho...
Numerical methods are the most popular tools in computational mechanics and have been used to tackle...
Julia is a high-level, high-performance dynamic programming language for numerical computing. This b...
Due to the computationally intensive nature of astrodynamics tasks, astrodynamicists have relied on...
Julia is a relatively new computer language that aims to reduce the challenge for mathmodelers to de...
The Julia Language is very easy to adopt for Research and Teaching. I found that this language is we...
We have experimented with Julia for the analysis of TESS data in cases where the speed of Python is ...
Machine learning is driving development across many fields in science and engineering. A simple and ...
Abstract. Execution speed is critical for code developed for high energy physics (HEP) research. HEP...
peer reviewedThis article presents the implementation of the material point method (MPM) using Julia...
This article describes how to develop a software test-bed to simulate the excution of instructions o...
This work describes dynamic programming language Julia. Firstly, user is introduced to syntax and im...