PPT-Near-Optimal Cache Block Placement with Reactive

Author : min-jolicoeur | Published Date : 2016-03-05

Nonuniform Cache Architectures Nikos Hardavellas Northwestern University Team M Ferdman B Falsafi A Ailamaki Northwestern Carnegie Mellon EPFL Hardavellas 2

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Near-Optimal Cache Block Placement with Reactive: Transcript

Nonuniform Cache Architectures Nikos Hardavellas Northwestern University Team M Ferdman B Falsafi A Ailamaki Northwestern Carnegie Mellon EPFL Hardavellas 2 Moores Law Is Alive And Well. Today’s topic. Cache performance assessment. Associative caches. Reminder. HW8 due next Friday 11/21/2014. HW9 . due Wednesday 12/03/2014. Grades so far. http://eecs.wsu.edu/~hassan/cs260/hws/CS260_Grades.pdf. CS448. 2. What is Cache Coherence?. Two processors can have two different values for the same memory location. Write Through Cache. 3. Terminology. Coherence. Defines what values can be returned by a read. Technique MR MP HT Complexity. Larger Block Size + – . 0. Higher Associativity + – 1. Victim Caches + 2. Pseudo-Associative Caches + 2. HW Prefetching of Instr/Data + 2. Compiler Controlled Prefetching + . Samira Khan . March 23, 2017. Agenda. Review from last lecture. Data flow model. Memory hierarchy. More Caches. The Dataflow Model (of a Computer). Von Neumann model: An instruction is fetched and executed in . Aakash. . Sabharwal. Section J. October. 7. th. , 2013. Welcome to the World of Pointers !. Class Schedule. Cache Lab. Due Thursday.. Start now ( if you haven’t already ). Exam Soon !. Start doing practice problems.. Why it works: The principle of locality. How it . works. : The architectural details. Von Neumann Architecture. Cost/performance analysis is a constant theme in computer engineering ‒ which is why the proper choice of performance metric is important. Michael . Moeng. Sangyeun. Cho. Rami. . Melhem. University of Pittsburgh. Background. Architects simulating more cores. Increasing . simulation . times. Cannot keep doing single-threaded . simulations if we want to see results in a reasonable time frame. With a superscalar, we might need to accommodate more than 1 per cycle. Typical server and . m. obile device. memory hierarchy. c. onfiguration with. b. asic sizes and. access times. PCs and laptops will. Direct-mapped caches. Set-associative caches. Impact of caches on performance. CS 105. Tour of the Black Holes of Computing. Cache Memories. C. ache memories . are small, fast SRAM-based memories managed automatically in hardware. March 28, 2017. Agenda. Review from last lecture. Cache access. Associativity. Replacement. Cache Performance. Cache Abstraction and Metrics. Cache hit rate = (# hits) / (# hits # misses) = (# hits) / (# accesses). Agenda. Review from last lecture. Data flow model. Memory hierarchy. More Caches. The Dataflow Model (of a Computer). Von Neumann model: An instruction is fetched and executed in . control flow order . Cache Memory and Performance Many of the following slides are taken with permission from Complete Powerpoint Lecture Notes for Computer Systems: A Programmer's Perspective (CS:APP) Randal E. Bryant Aditya Shah. Recitation 7: Oct . 8. th. , 2015. Welcome to the World of Pointers !. Outline. Schedule. Memory . organization. Caching. Different . types of locality. Cache organization. Cache lab. Part (a) Building Cache Simulator. Nonuniform. Cache Architectures. Nikos Hardavellas, Northwestern University. Team: M. Ferdman,. . B. Falsafi,. . A. . Ailamaki. Northwestern, Carnegie Mellon, EPFL. © Hardavellas. 2. Moore’s Law Is Alive And Well.

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