PPT-Scalable Multiprocessors

Large scale computing systems Scalability issues Low level and high level communication abstractions in scalable systems Network interface Common techniques for high performance communication. 1 Multiprocessor System Interconnects Generalized Multiprocessor System Generalized Multiprocessor System Each processor Pi is attached to its own local memory and private cache Multiple processors connected to shared memory through interprocessor me 1 Multiprocessors 82 Multicomputers 83 Distributed systems Multiprocessor Systems Continuous need for faster computers shared memory model message passing multiprocessor wide area distributed system Multiprocessors Definition A computer system in wh 142 brPage 2br Taxonomy SISD single instruction and sing le data stream uniprocessor MISD no commercial multiprocessor imagine data going through a pipeline of execution engines SIMD vector architectures lower flexibility MIMD most multiprocessors to Clements M Frans Kaashoek Nickolai Zeldovich Robert T Morris and Eddie Kohler MIT CSAIL and Harvard University Abstract What fundamental opportunities for scalability are latent in interfaces such as system call APIs Can scalability opportunities b ADVANTAGES SCALABLE:Cost effective monitoring from tens to tens of thousands of servers and devices. EXTENSIBLE:Architected to integrate with the rest of your data center, as it amalgamates best-of-br
\n \r\r !\r"$#%&(')*+!,-!%.%"%/01325476d981U David . Kaser. Lecture Series. Lorcan Dempsey / . @. LorcanD. Indiana University, . 7 October 2012. How terrific to see you are the featured lecturer this year.   Just thought I'd mention that David . Commutativity. Rule: Designing Scalable Software for Multicore Processors. Austin T. Clements, M. . Frans. . Kaashoek. , . Nickolai. . Zeldovich. , Robert T. Morris, and Eddie Kohler. MIT CSAIL and Harvard University. Processors. Presented by . Remzi. Can . Aksoy. *Some slides . are. . borrowed from a ‘Papers We Love’ . Presentation. EECS 582 – F16. 1. Outline. The . Scalable Commutativity Rule: . Whenever interface operations commute, they can be implemented in a way that scales. Luis . Herranz. Arribas. Supervisor: Dr. José M. Martínez Sánchez. Video Processing and Understanding Lab. Universidad . Aut. ónoma. de Madrid. Outline. Introduction. Integrated. . summarization. FOR CHILDREN OF ABUSE, NEGLECT & ABANDONMENT”. CONFRONTING ABUSE – CHANGING LIVES. BUILDING A SCALABLE & SUSTAINABLE SUPPORT STRUCTURE. Scott Murrish. ScottMurrish.com. 308-440-4560. . BUILDING A SCALABLE & SUSTAINABLE SUPPORT STRUCTURE. Larry Peterson. In collaboration with . Arizona. , Akamai. ,. . Internet2. , NSF. , North Carolina, . Open Networking Lab, Princeton. (and several pilot sites). S3. DropBox. GenBank. iPlant. Data Management Challenge. Introduction. Multiprocessing.  is the use of two or more . central processing units.  (CPUs) within a single . computer . system. . The . term also refers to the ability of a system to support more than one processor and/or the ability to allocate tasks between them. COS 418: Distributed Systems. Lecture . 14. Wyatt Lloyd. Consistency Hierarchy. Linearizability. Sequential Consistency. Causal+ Consistency. Eventual Consistency. e.g., RAFT. e.g., Bayou. e.g., Dynamo.