دانلود رایگان مقاله انگلیسی موضوع ویژه در مورد معماری کامپیوتر و محاسبات با کارایی بالا - الزویر 2018

عنوان فارسی
موضوع ویژه در مورد معماری کامپیوتر و محاسبات با کارایی بالا
عنوان انگلیسی
Special issue on Computer Architecture and High Performance Computing
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
1
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
نوع نگارش
Editorial
رفرنس
دارد
پایگاه
اسکوپوس
کد محصول
E10198
رشته های مرتبط با این مقاله
مهندسی کامپیوتر
گرایش های مرتبط با این مقاله
معماری کامپیوتر
مجله
مجله محاسبات موازی و توزیع شده - Journal of Parallel and Distributed Computing
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.jpdc.2018.07.016
بخشی از متن مقاله

This special issue is focused on Computer Architecture and High Performance Computing. It also includes extended papers presented at SBAC-PAD 2016, 28th International Symposium on Computer Architecture and High Performance Computing, which took place in Los Angeles, USA, from October 26–28, 2016. All submitted papers to this special issue were rigorously reviewed by at least three expert reviewers, and further carefully evaluated by the guest editors. After the review process, only 9 papers were finally accepted for publication. Below, we provide an overview of the papers appearing in this volume. In ‘‘Janus: Diagnostics and Reconfiguration of Data Parallel Programs’’, the authors present the design and implementation of Janus, a tool that automates the reconfiguration of Spark applications. It leverages logs from previous executions as input, enforces configurable adjustment policies over the collected statistics and makes its decisions taking into account communication behaviors specific of the application evaluated, showing gains of up to 1.9x in the scenarios considered. The work entitled ‘‘An Experimental Evaluation of a Parallel Simulated Annealing Approach for the 0–1 Multidimensional Knapsack Problem’’ focuses on the proposal of a parallel simulated annealing algorithm (SA) using GPGPU. The results achieved by the parallel SA were compared to other reference works and showed that GPGPU is effective on the task of obtaining better quality solutions in reduced execution time when compared to sequential programs.


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