'Transactional memory' diaporamas de présentation

Is Transactional Memory an Oxymoron?

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Debugging Programs that use Atomic Blocks and Transactional Memory

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Motivation

Transactional Memory Prof. Hsien-Hsin S. Lee School of Electrical and Computer Engineering Georgia Tech (Adapted from Stanford TCC group and MIT SuperTech Group). Motivation. Uniprocessor Systems Frequency Power consumption Wire delay limits scalability

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Parallelism and Concurrency

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CS6068 Parallel Computing: Fall 2015 - Week 2 Parallel Computing Patterns

CS6068 Parallel Computing: Fall 2015 - Week 2 Parallel Computing Patterns. Readings - Topics. The Landscape of Parallel Computing ( UC Berkeley perspective) http:// www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-183.pdf The Berkeley Par Lab B ook

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Conference Review Presented by: Utku Aydonat

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An Effective Hybrid Transactional Memory System with Strong Isolation Guarantees

An Effective Hybrid Transactional Memory System with Strong Isolation Guarantees. Minh, Trautmann , Chung, McDonald, Bronson, Casper, Kozyrakis , Olukotun. Presented by Cynthia Sturton 5/5/08. Outline. Software Transactional Memory Hardware Transactional Memory SigTM.

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Read-Write Lock Allocation in Software Transactional Memory

Read-Write Lock Allocation in Software Transactional Memory. Amir Ghanbari Bavarsad and Ehsan Atoofian Lakehead University. Transactional Memory. Software transactional memory (STM) exploits a global clock to validate transactional data Pros: reduces validation overhead Cons: contention

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Alternatives to Locks

Alternatives to Locks. Presented by Isaac Charles 11/18/05. Outline. Review: locking techniques Review: synchronization primitives Non-blocking algorithms Transactional Memory Software Contention Managers Hardware. Locking Techniques.

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Programming Heterogeneous (GPU) Systems

Programming Heterogeneous (GPU) Systems. Jeffrey Vetter. Presented to Extreme Scale Computing Training Program ANL: St. Charles, IL 2 August 2013 . http:// ft.ornl.gov ? vetter@computer.org. TH-2 System. Compute Nodes have 3.432 Tflop /s per node 16,000 nodes 32000 Intel Xeon cpus

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Programming Heterogeneous (GPU) Systems

Programming Heterogeneous (GPU) Systems. Jeffrey Vetter. Presented to Extreme Scale Computing Training Program ANL: St. Charles, IL 2 August 2013 . http:// ft.ornl.gov ? vetter@computer.org. TH-2 System. Compute Nodes have 3.432 Tflop /s per node 16,000 nodes 32000 Intel Xeon cpus

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Exploring the relations between STM and DB consistency conditions

Exploring the relations between STM and DB consistency conditions. Sandeep Hans TransForm @ Technion Joint work with Hagit Attiya. Database vs. STM. Database. STM. Beyond Serializability. Recoverability Avoiding Cascading Aborts Strictness Rigorousness. RC. ACA. ST. RG.

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Transactional Memory

Transactional Memory. Concurrency unlocked Programming. Outline. Background Motivation Database Transaction Transactional Memory History Transactional Memory Example Mechanisms Software Transactional Memory Hardware Transactional Memory Application. Background.

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Why The Grass May Not Be Greener On The Other Side: A Comparison of Locking vs. Transactional Memory By McKenney, Micha

Why The Grass May Not Be Greener On The Other Side: A Comparison of Locking vs. Transactional Memory By McKenney, Michael, Triplett and Walpole. Agenda. Locking Critique TM Critique Need for a combined approach. Locking. Simple approach based on mutual exclusion:

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Unbounded Transactional Memory

Unbounded Transactional Memory. Paper by Ananian et al. of MIT CSAIL Presented by Daniel. Outline. Motivation UTM vs LTM UTM in detail Processor changes Transaction state data structure Operational description LTM changes required description Simulation Results. Motivation.

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Good Programming in Transactional Memory Game Theory Meets Multicore Architecture

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Lecture 1: Introduction

Lecture 1: Introduction. Course organization: 4 lectures on cache coherence and consistency 2 lectures on transactional memory 2 lectures on interconnection networks 4 lectures on caches 4 lectures on memory systems 4 lectures on core design 2 lectures on parallel algorithms

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Challenges in Concurrent Computing

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Privatization Techniques for Software Transactional Memory

Privatization Techniques for Software Transactional Memory. Michael F. Spear, Virendra J. Marathe , Luke Dalessandro, and Michael L. Scott University of Rochester. Motivation for Privatization. Limitations of Memory Transactions Semantic limitations (cannot permit I/O in txns)

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Memory is the Network

Memory is the Network. Krste Asanovic The Parallel Computing Laboratory EECS Department UC Berkeley. NoCS Panel, May 13, 2009. One Slide Version of Talk. No-one can afford to build application-specific chips at least not in feature sizes that warrant a NoC

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