PPT-Ameliorating Memory Contention of OLAP Operators on GPU Processors

Evangelia A Sitaridi Kenneth A Ross Columbia University DaMoN Workshop 21st May 2012 Introduction 12 Earlier GPU implementations of data processing operators have resulted in significant speedups. ca Abstract Contention for shared resources on multicore processors remains an unsolved problem in existing systems despite signi64257cant re search efforts dedicated to this problem in the past Previous solu tions focused primarily on hardware techn John Mellor-Crummey and Michael Scott. Presented by Shoaib Kamil. Overview. Review of some lock types. MCS lock algorithm. Barriers. Empirical Performance. Discussion. Review of Lock Types. test&set. 2. Processor development till 2004. Out-of-order. Instruction scheduling. 3. Why multi-core ?. Difficult to make single-core. clock frequencies even . higher – heat problems . Deeply pipelined circuits:. Improving Computer Performance. What performance translates into:. Time taken to do computation. Improving performance . → reducing time taken. What key benefits improving performance can bring:. Can solve “now-computationally-attainable” problems in . Contents . Vector processor. Vector instructions. Vector pipelines. Scalar pipeline execution. Vector pipeline execution. Symbolic processors. Attributes. Characteristics. Vector Processors. A vector processor is specially designed to perform vector computations.. 2. Processor development till 2004. Out-of-order. Instruction scheduling. 3. Why multi-core ?. Difficult to. increase. . clock . frequencies even . higher – heat . problems. . Moore’s law is at its limits. Thread Level Parallelism. Chapter 4, Appendix H. CS448. 2. The Greed for Speed. Two general approaches to making computers faster. Faster uniprocessor. All the techniques we’ve been looking at so far, plus others…. Presented By:. Rahul. M.Tech. CSE, GBPEC . Pauri. Contents. Introduction. Symmetric memory architecture. Advantages. The limitations. Addressing the limitations. Problem with more than one copy in caches. Définition. La contention a pour objectif de limiter les capacités de mobilisation d’un individu de manière à le sécuriser ou protéger son environnement. Recouvrant différents aspects, elle doit néanmoins rester exceptionnelle et s’associer à d’autres prises en charges thérapeutiques. . Evangelia A. Sitaridi, Kenneth A. Ross. Columbia University. DaMoN Workshop. 21st May 2012. . Introduction (1/2). Earlier GPU implementations of data processing operators have resulted in significant speedups. Why the Grass May Not Be Greener on the Other Side: A Comparison of Locking and Transactional Memory. Why Do Concurrent Programming?. Hardware has been forced down the path of concurrency:. can’t make cores much faster. 2/8/2018. Introduction to Advanced Processors. 1. Outline . Features. Internal Architecture of 80286. Interrupts of . 80286. Signal Description of . 80286. Real And Protected Mode. Instruction set. 2/8/2018. Tennessee State University. 2017. 年. 6. 月. at. 法政大学. 1. Lectures on Parallel and Distributed Computing . 2. Lecture . 1: Introduction to parallel . computing . Lecture 2: Parallel . computational models. Massively Parallel Processors. Instructor:Mikko. H . Lipasti. Spring 2017. University of Wisconsin-Madison. Lecture notes based on slides created by John . Shen. , Mark Hill, David Wood, . Guri. . Sohi.