کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4956868 | 1364714 | 2016 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fitting processor architectures for measurement-based probabilistic timing analysis
ترجمه فارسی عنوان
معماری پردازنده را برای تجزیه و تحلیل احتمالاتی بر اساس اندازه گیری بر اساس
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کلمات کلیدی
زمان اجرای بدترین حالت، معماری پردازنده، حافظه پنهان، تجزیه و تحلیل احتمالی، تصادف زمان،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
The pressing market demand for competitive performance/cost ratios compels Critical Real-Time Embedded Systems industry to employ feature-rich hardware. The ensuing rise in hardware complexity however makes worst-case execution time (WCET) analysis of software programs - which is often required, especially for programs at the highest levels of integrity - an even harder challenge. State-of-the-art WCET analysis techniques are hampered by the soaring cost and complexity of obtaining accurate knowledge of the internal operation of advanced processors and the difficulty of relating data obtained from measurement observations with reliable worst-case behaviour. This frustrating conundrum calls for novel solutions, with low intrusiveness on development practice. Measurement-Based Probabilistic Timing Analysis (MBPTA) techniques offer the opportunity to simultaneously reduce the cost of acquiring the knowledge needed for computing reliable WCET bounds and gain increased confidence in the representativeness of measurement observations. This paper describes the changes required in the design of several high-performance features - massively used in modern processors - to meet MBPTA requirements.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microprocessors and Microsystems - Volume 47, Part B, November 2016, Pages 287-302
Journal: Microprocessors and Microsystems - Volume 47, Part B, November 2016, Pages 287-302
نویسندگان
Leonidas Kosmidis, Eduardo Quiñones, Jaume Abella, Tullio Vardanega, Carles Hernandez, Andrea Gianarro, Ian Broster, Francisco J. Cazorla,