Authors may use MDPI'sĮnglish editing service prior to publication or during author revisions.įor parallelization of applications with high processing times and large amounts of storage in High Performance Computing (HPC) systems, shared memory programming and distributed memory programming have been used a parallel application is represented by Parallel Task Graphs (PTGs) using Directed Acyclic Graphs (DAGs). Submitted papers should be well formatted and use good English. The Article Processing Charge (APC) for publication in this open access journal is 2300 CHF (Swiss Francs). Please visit the Instructions for Authors page before submitting a manuscript. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. All manuscripts are thoroughly refereed through a single-blind peer-review process. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Research articles, review articles as well as short communications are invited. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. All submissions that pass pre-check are peer-reviewed. Manuscripts can be submitted until the deadline. Once you are registered, click here to go to the submission form. Manuscripts should be submitted online at by registering and logging in to this website.
The focus will be on applications involving parallel methods of solving hard computational problems, especially of optimization. This Special Issue is devoted to topics in parallel computing, including theory and applications.
The main target of parallel computing is scientific applications, and many large-scale scientific applications refer to problems that are modeled as optimization problems, often discrete ones, based on graph modeling and exploiting artificial intelligence methods. It is an effective method to improve the computing speed and processing power of computer systems. Over the past few years, parallel computing has been widely used to solve computational problems, especially in optimization.
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