18 740 Computer Architecture Lecture 14 Multi Core Memory Architectures Resource Management

Ppt Multi Core Architectures And Shared Resource Management Lecture 1 Subscribed 23 1.7k views 9 years ago lecture 14: multi core memory architectures & resource management lecturer: prof. onur mutlu ( users.ece.cmu.edu ~omutlu ). Kim et al., “fair cache sharing and partitioning in a chip multiprocessor architecture,” pact 2004. 8 example: problem with shared caches processor core 1 ←t1 t2→ l1 $ processor core 2 l1 $ l2 $ …… t2’s throughput is significantly reduced due to unfair cache sharing.

15 74018 740 Computer Architecture Lecture 13 More Resource sharing concept n idea: instead of dedicating a hardware resource to a hardware context, allow multiple contexts to use it q n example resources: functional units, pipeline, caches, buses, memory why? resource sharing improves utilization efficiency throughput q when a resource is left idle by one thread, another thread can use it. This channel contains lecture videos and slides from computer architecture courses taught by professor onur mutlu ( people.inf.ethz.ch omutlu ) at carnegie mellon university. Goal 1: " build a strong understanding of the fundamentals of the multi core architectures and the tradeoffs made in their design. " examine how cores and shared resources can be designed. " the focus will be on fundamentals, tradeoffs in parallel architecture design, and cutting edge research. goal 2:. Shared resources among multiple cores: how to design and manage? parallel programming: how to write programs that can benefit from multiple cores? how to ease parallel programming? how to design the cores: what kind? homogeneous or heterogeneous? how to design the interconnect between cores caches memory? why the disparity in slowdowns?.

Computer Architecture Lecture 4 Memory Computer Architecture Goal 1: " build a strong understanding of the fundamentals of the multi core architectures and the tradeoffs made in their design. " examine how cores and shared resources can be designed. " the focus will be on fundamentals, tradeoffs in parallel architecture design, and cutting edge research. goal 2:. Shared resources among multiple cores: how to design and manage? parallel programming: how to write programs that can benefit from multiple cores? how to ease parallel programming? how to design the cores: what kind? homogeneous or heterogeneous? how to design the interconnect between cores caches memory? why the disparity in slowdowns?. This course qualitatively and quantitatively examines fundamental computer design trade offs, with the goal of developing an understanding that will enable students to perform cutting edge research in computer architecture. What these mini lecture series is about • multi core architectures and shared resource management: fundamentals and recent research • memory systems in the multi core era • a very “hot” portion of computer architecture research and practice • a very large design space • many opportunities for innovation and groundbreaking research. Memory subsystem: main memory dram, multi core cache hierarchy and shared memory management (coherence and consistency models). newer research topics like ai accelarators, neuromorphic computing, other industry trends and competitive dynamics. Challenge 1: how to provide high memory bandwidth to computation units in a practical way? processing in memory based on 3d stacked dram challenge 2: how to design computation units that efficiently exploit large memory bandwidth?.