کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4951561 1441479 2017 22 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic and discrete cache insertion policies for managing shared last level caches in large multicores
ترجمه فارسی عنوان
سیاست های درج کش پویا و گسسته برای مدیریت مخازن ذخیره شده گذشته در چندین مرتبه
کلمات کلیدی
شماره پدیده، اولویت های گسسته، هسته بیشتر از وابستگی، دور زدن مدیریت کش، منابع مشترک،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی
Multi-core processors employ shared Last Level Caches (LLC). This trend will continue in the future with large multi-core processors (16 cores and beyond) as well. At the same time, the associativity of LLC tends to remain in the order of sixteen. Consequently, with large multicore processors, the number of applications or threads that share the LLC becomes larger than the associativity of the cache itself. LLC management policies have been extensively studied for small scale multi-cores (4-8 cores) and associativity degree in the 16 range. However, the impact of LLC management on large multi-cores is essentially unknown, in particular when the associativity degree is smaller than the number of applications. In this study, we introduce Adaptive Discrete and deprioritized Application PrioriTization (ADAPT), an LLC management policy addressing the large multi-cores where the LLC associativity degree is smaller than the number of applications. ADAPT builds on the use of the Footprint-number metric. We propose a monitoring mechanism that dynamically samples cache sets to estimate the Footprint-number of applications and classify them into discrete (distinct and more than two) priority buckets. The cache replacement policy leverages this classification and assigns priorities to cache lines of applications during cache replacement operations. We further find that de-prioritizing certain applications during cache replacement is beneficial to the overall performance. We evaluate our proposal on 16, 20 and 24-core multi-programmed workloads and discuss other aspects in detail.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Parallel and Distributed Computing - Volume 106, August 2017, Pages 215-226
نویسندگان
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