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Research Issues/Challenges to Systems Software for Multicore and Data-Intensive Applications

Research Issues/Challenges to Systems Software for Multicore and Data-Intensive Applications

Research Issues/Challenges to Systems Software for Multicore and Data-Intensive Applications. Xiaodong Zhang Ohio State University In collaboration with F. Chen, X. Ding , Q. Lu, P. Sadayappan, Ohio State S. Jiang, Wayne State University, Z. Zhang, Iowa State

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714 views • 60 slides
Research Issues/Challenges to Systems Software for Multicore and Data-Intensive Applications

Research Issues/Challenges to Systems Software for Multicore and Data-Intensive Applications

Research Issues/Challenges to Systems Software for Multicore and Data-Intensive Applications. Xiaodong Zhang Ohio State University In collaboration with F. Chen, X. Ding , Q. Lu, P. Sadayappan, Ohio State S. Jiang, Wayne State University, Z. Zhang, Iowa State

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697 views • 60 slides
Outline

Outline

Outline. Introduction Background Distributed DBMS Architecture Distributed Database Design Semantic Data Control Distributed Query Processing Distributed Transaction Management Data server approach Parallel architectures Parallel DBMS techniques Parallel execution models

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614 views • 42 slides
10. Parallel Database Systems

10. Parallel Database Systems

10. Parallel Database Systems. Chapter 14 Parallel Database Systems. Fact and Database Problem. A large volume of data uses disk and large main memory Speed(disk) << speed(RAM) << speed(microprocessor). The Solution. Increase the I/O bandwidth Data partitioning Parallel data access

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1.69k views • 41 slides
Parallel DBMS

Parallel DBMS

Parallel DBMS. Chapter 22, Part A. Slides by Joe Hellerstein, UCB, with some material from Jim Gray, Microsoft Research. See also: http://www.research.microsoft.com/research/BARC/Gray/PDB95.ppt. Why Parallel Access To Data?. At 10 MB/s 1.2 days to scan. 1,000 x parallel

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239 views • 22 slides
Parallel DBMS

Parallel DBMS

Parallel DBMS. DBMS Textbook Chapter 22. Slides adapted from textbook; from Joe Hellerstein; and from Jim Gray, Microsoft Research. Why Parallel Access To Data?. At 10 MB/s 1.2 days to scan. 1,000 x parallel 1.5 minute to scan. 1 Terabyte. Bandwidth. 1 Terabyte. 10 MB/s.

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240 views • 21 slides
A Comparison of Approaches to Large-Scale Data Analysis

A Comparison of Approaches to Large-Scale Data Analysis

A Comparison of Approaches to Large-Scale Data Analysis. Andrew Pavlo, Erik Paulson, Alexander Rasin, Daniel J. Abadi, David J. Dewitt, Samuel Madden, Michael Stonebraker SIGMOD 2009 2009-10-09 Summarized by Jaeseok Myung. Intelligent Database Systems Lab

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451 views • 20 slides
C-Store: Data Management in the Cloud

C-Store: Data Management in the Cloud

C-Store: Data Management in the Cloud. Jianlin Feng School of Software SUN YAT-SEN UNIVERSITY Jun 5, 2009. What is the Cloud?. A definition from Wikipedia

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273 views • 17 slides
Mapping the Data Warehouse to a Multiprocessor Architecture

Mapping the Data Warehouse to a Multiprocessor Architecture

Mapping the Data Warehouse to a Multiprocessor Architecture. By N.Gopinath AP/CSE. Mapping the Data Warehouse to a Multiprocessor Architecture. The goals of linear performance and scalability can be satisfied by parallel hardware architectures, parallel operating systems, and parallel DBMSs.

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667 views • 6 slides

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