PPT-Ameliorating Memory Contention of OLAP Operators on GPU Pro

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. . Acknowledgement: the lecture materials are based on the materials in NVIDIA teaching center CUDA course materials, including materials from Wisconsin (. Negrut. ), North Carolina Charlotte (. Wikinson. Dr A . Sahu. Dept of Comp Sc & . Engg. . . IIT . Guwahati. 1. Outline. Graphics System . GPU Architecture. Memory Model. Vertex Buffer, Texture buffer. GPU Programming Model. DirectX. , OpenGL, . Alan . Gray. EPCC . The University of Edinburgh. Outline. Why do we want/need accelerators such as GPUs?. Architectural reasons for accelerator performance advantages . Latest accelerator Products. NVIDIA and AMD GPUs. MATTHEW 12:34. Contention and Strife. Hebrew . RIB. physical struggle . Ex. 21:18. Verbal contention . Judges 6:32 . Waters of . Me. RIB. ah. . Ex. 17:7. Legal disputes . Deut. 25:1, Prov. 25:8-10. Questions to consider. What is the central message the author is trying to convey to his/her audience?. What is the main point the author is trying to convince me of?. 1. Look at the title.. What is the message it is conveying?. Alma 3. Alma 3. Mosiah 2. Wages. Civil War- Atonement and Contention. 3 Nephi 11. Elder Bednar. Interestingly, the admonition to “be ye therefore perfect” is immediately preceded by counsel about how we should act in response to wrongdoing and offense. Clearly, the rigorous requirements that lead to the perfecting of the Saints include assignments that test and challenge us. . Sathish. . Vadhiyar. Parallel Programming. GPU. Graphical Processing Unit. A single GPU consists of large number of cores – hundreds of cores.. Whereas a single CPU can consist of 2, 4, 8 or 12 cores. 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. . Lecture 2: more basics. Recap. Can use GPU to solve highly parallelizable problems. Straightforward extension to C++. Separate CUDA code into .cu and .. cuh. files and compile with . nvcc. to create object files (.o files). Evangelia Sitaridi, . Thesis Defense. Columbia University . GPUs for Social Media Analytics. 2. Search terms: . Match . regexp. : “/\B#\w*[a-. zA. -Z] \w*/ . . debate. Filter location. More GPU Data Analytics Use-Cases. Add GPUs: Accelerate Science Applications. © NVIDIA 2013. Small Changes, Big Speed-up. Application Code. . GPU. C. PU. Use GPU to Parallelize. Compute-Intensive Functions. Rest of Sequential. CPU Code. 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. Within your language analysis, one of the first things that you need to establish is the recognition of the . issue or event. . that the writer is referring to, as well as the . contention. or the writer’s point of view on it. . A Tale of Two Cities: GPU Computing and Machine Learning Dr. Xiaowen Chu Department of Computer Science, Hong Kong Baptist University Outline 2 Some Stories of “Two Cities” Evolution of CPUs/