دانلود مقاله ISI انگلیسی شماره 78468
ترجمه فارسی عنوان مقاله

SoPHy+: مدل برنامه نویسی و پلت فرم نرم افزار برای مدیریت منابع ترکیبی از شتاب دهنده many-core

عنوان انگلیسی
SoPHy+: Programming model and software platform for hybrid resource management of many-core accelerators
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
78468 2016 12 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Microprocessors and Microsystems, Volume 43, June 2016, Pages 47–58

ترجمه کلمات کلیدی
شتاب دهنده Many-core - توان؛ پلت فرم نرم افزار؛ مدیریت منابع؛ نقشه برداری زمان اجرا
کلمات کلیدی انگلیسی
Many-core accelerator; Throughput; Software platform; Resource management; Run-time mapping
پیش نمایش مقاله
پیش نمایش مقاله  SoPHy+: مدل برنامه نویسی و پلت فرم نرم افزار برای مدیریت منابع ترکیبی از شتاب دهنده many-core

چکیده انگلیسی

As demand of higher computing power is steadily increasing, it becomes popular to equip a many-core accelerator in a computer system to run concurrent applications. Efficient management of compute resources in such a system is challenging because various factors such as workload variation, QoS requirement change, and hardware failure may cause dynamic change in system status. Recently, a variety of resource management techniques for many-core accelerators have been proposed. They are usually tailored for a specific target architecture. In this paper, we present SoPHy+, which supports various types of many-core accelerators, based on a hybrid resource management technique. SoPHy+ provides a seamless design flow from programming front-end, which generates dataflow-style function codes automatically from the task specification, to run-time environment, which adaptively manages compute resources for concurrent applications in response to system status change. SoPHy+ has been implemented on two different many-core architectures: the Intel Xeon Phi coprocessor and an Epiphany-like NoC virtual prototype. Experimental results prove that SoPHy+ is capable of adapting to the run-time workload variation effectively with affordable overhead of run-time resource management.