'Global synchronization' presentation slideshows

Titanium: A Java Dialect for High Performance Computing

Titanium: A Java Dialect for High Performance Computing. Katherine Yelick U.C. Berkeley and LBNL. Motivation: Target Problems. Many modeling problems in astrophysics, biology, material science, and other areas require Enormous range of spatial and temporal scales

855 views • 74 slides

Titanium: From Java to High Performance Computing

Titanium: From Java to High Performance Computing. Katherine Yelick U.C. Berkeley and LBNL. Motivation: Target Problems. Many modeling problems in astrophysics, biology, material science, and other areas require Enormous range of spatial and temporal scales

629 views • 55 slides

Titanium: A Java Dialect for High Performance Computing

Titanium: A Java Dialect for High Performance Computing. Katherine Yelick U.C. Berkeley and LBNL. Motivation: Target Problems. Many modeling problems in astrophysics, biology, material science, and other areas require Enormous range of spatial and temporal scales

652 views • 51 slides

GPU Programming and CUDA

574 views • 45 slides

AQM & TCP models

AQM & TCP models. Courtesy of Sally Floyd with ICIR Raj Jain with OSU. Agenda. Queue management Passive Active AQM: RED Variants ECN TCP models. the majority in router. Passive queue management (PQM) No preventive packet drop Buffer level > threshold, drop packets

536 views • 42 slides

6.852: Distributed Algorithms Spring, 2008

527 views • 40 slides

Optimizing Parallel Reduction in CUDA

632 views • 38 slides

Optimizing Parallel Reduction in CUDA

401 views • 38 slides

Global Clock Synchronization in Sensor Networks

Global Clock Synchronization in Sensor Networks. Qun Li, Member, IEEE, and Daniela Rus, Member, IEEE. IEEE Transactions on Computers 2006. Chien-Ku Lai. Outline. Introduction The Synchronization Problem All-Node-Based Synchronization Cluster-Based Synchronization Synchronous Diffusion

496 views • 36 slides

Architectural Support for System Software on Large-Scale Clusters

464 views • 35 slides

Architectural Support for System Software on Large-Scale Clusters

481 views • 35 slides

Ultra-Low Power Time Synchronization Using Passive Radio Receivers

427 views • 31 slides

Random Early Detection Gateways for Congestion Avoidance

Random Early Detection Gateways for Congestion Avoidance. Sally Floyd and Van Jacobson, IEEE Transactions on Networking , Vol.1, No. 4, (Aug 1993), pp.397-413. Outline. Introduction Background: Definitions and Previous Work The RED Algorithm RED parameters Evaluation of RED

343 views • 27 slides

Random Early Detection Gateways for Congestion Avoidance

Random Early Detection Gateways for Congestion Avoidance. Jinyoung You CS540, Network Architect. Contents. Introduction of the Problem Previous works Design goals of the RED gateway The RED algorithm Simulation Results Calculation Parameter sensitivity Conclusions. Problem.

261 views • 26 slides

Active Queue Management

Active Queue Management. Fundamental problem: Queues and TCP. Queues Queues are to absorb bursts of packets. They are required for statistical multiplexing. Queuing theory shows how far higher throughput is possible if queues are included. M/M/1/K queue =>.

515 views • 20 slides

CSE679: Buffer Management

CSE679: Buffer Management. Drop Tail RED Advanced RED. Network Congestion. Congestion results in buffer backlog Eventually, packets have to be dropped Packet drops indicate congestion to senders Senders eventually backoff to reduce congestion

306 views • 15 slides

EE689 Lecture 5

EE689 Lecture 5. Review of last lecture More on HPF RED. Network Congestion. Congestion results in buffer backlog Eventually, packets have to be dropped Packet drops indicate congestion to senders Senders eventually backoff to reduce congestion

254 views • 14 slides

Queueing Problem

to next router. (drop-tail) queue. server. packet losses. Queueing Problem. The performance of network systems rely on different delays. Propagation/processing/transmission/queueing delays Which delay is affected most by network congestion? Queueing delay.

251 views • 7 slides

1. Project Goal (SISA Omni-OS)

1. Project Goal (SISA Omni-OS). Project Goal - Develop an Operating System that will scale to 80% efficiency at 1000+ cores by 2015 and support a transition path from Linux and GNU based ecosystem (2011) 50%@48 --> (2013) 80%@100 cores incrementing up to 80%@1000 cores by 2015

155 views • 3 slides

U.C. Berkeley and LBNL

Compiler-generated code. Compiler-specific runtime system. GASNet Extended API. GASNet Core API. Network Hardware. Distributed Data Structures. U.C. Berkeley and LBNL. http://upc.nersc.gov. upc@lbl.gov. Christian Bell, Dan Bonachea, Wei Chen, Jason Duell, Paul Hargrove,

126 views • 1 slides