مقاله انگلیسی رایگان در مورد افزایش قابلیت اطمینان تحلیل زمان‌بندی نرم افزار برای پردازنده های مبتنی بر حافظه نهان – 2019 IEEE

 

مشخصات مقاله
ترجمه عنوان مقاله افزایش قابلیت اطمینان تحلیل زمان‌بندی نرم افزار برای پردازنده های مبتنی بر حافظه نهان
عنوان انگلیسی مقاله Increasing the Reliability of Software Timing Analysis for Cache-Based Processors
انتشار مقاله سال 2019
تعداد صفحات مقاله انگلیسی 16 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) Master Journal List – JCR – Scopus
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
4.136 در سال 2018
شاخص H_index 110 در سال 2019
شاخص SJR 0.831 در سال 2018
شناسه ISSN 0018-9340
شاخص Quartile (چارک) Q1 در سال 2018
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط کامپیوتر
گرایش های مرتبط مهندسی الگوریتم ها و محاسبات، مهندسی نرم افزار، هوش مصنوعی، معماری سیستم های کامپیوتری
نوع ارائه مقاله
ژورنال
مجله نتایج بدست آمده در حوزه رایانه ها – Transactions on Computers
دانشگاه Barcelona Supercomputing Center (BSC), Barcelona, Spain
کلمات کلیدی سیستم های بلادرنگ جاسازی شده، حافظه های پنهان، اعتبار سنجی و تأیید زمان بندی
کلمات کلیدی انگلیسی Embedded real-time systems، cache memories، timing validation and verification
شناسه دیجیتال – doi
https://doi.org/10.1109/TC.2018.2890626
کد محصول E13095
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract

1- Introduction

2- Timing V&V, Certification, and Standards

3- Understanding CCP under RM and HRP

4- The CCP-RM Mechanism

5- The CCP-HRP Mechanism

6- EVIDENCE FOR CERTIFICATION

7- RAILWAY CASE STUDY ON FPGA

8- RELATED WORK

9- CONCLUSIONS

References

 

بخشی از متن مقاله:

Abstract

Real-time systems are witnessing a significant increase in critical software’s size, complexity, and performance needs, which can only be satisfied with high-performance hardware features. Cache memories, pervasively used to improve average performance, complicate Worst-Case Execution Time analysis: cache placement (i.e., how software objects are mapped to cache) during the testing phase does not only critically affect the observed performance, but also proves to be arduous to control and preserve up to operation. The probabilistic variant of Measurement-Based Timing Analysis (MBPTA) responds to this challenge by deploying time-randomized caches that naturally explore a different random cache placement in each run, relieving the user from producing tests that intercept relevant Cache Conflict Placements (CCP). Yet, to meet an adequate probabilistic CCP coverage, the user is required to collect a minimum number of measurements. We present two mechanisms, CCP-RM and CCP-HRP, to identify CCP with relevant probability of occurrence and large impact on execution-time, for the random modulo (RM) and hash-based random placement (HRP) policies. CCP-RM and CCP-HRP enable a reliable application of MBPTA by computing the number of runs R ‘ necessary to meet the desired CCP coverage. We exhaustively evaluate CCP-RM and CCP-HRP, showing their effectiveness on well-known benchmarks and a railway case study, on top of an accurate simulator and a concrete RTL implementation.

INTRODUCTION

In critical-embedded real-time systems [34] software continues to be in charge of providing most innovative services, making it instrumental in increasing products’ competitive edge in the market [23]. Software is also increasingly driving the decision making process over a huge amounts of data of diverse types, which not only increases its complexity but also complicates timing validation and verification (V&V). The latter focus on providing evidence that system functions perform timely: to that end, timing analysis methods are used to estimate the worst-case execution time (WCET) of tasks. WCET estimates must be reliable, according to the level of confidence defined in the relevant safety standards, and as tight as possible, to minimize the provisioning of hardware resources. Timing V&V is further challenged by the use of performance-accelerating hardware (e.g., caches) to provide the unprecedented rise in performance needs for critical software’s, expected to be as high as 100x in the next years in the automotive domain [1]. Increased hardware and software complexity reduces the confidence that can be placed on WCET estimates derived by measurement-based timing analysis (MBTA), the most used timing analysis technique in critical real-time embedded systems [44]. In particular, increased effort is needed on the user to concoct stressing execution scenarios during the (analysis-time) test campaign as a means to capture bad scenarios that can arise during system operation [18].

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