'Massive data sets' presentation slideshows

Massive data sets - PowerPoint PPT Presentation


Cybertools!!

Cybertools!!

Cybertools!!. David DeWitt. So what is a cybertool?. That is a good question NSF doesn’t even know the answer Maybe Hector does since he wrote the report However, NSF is about to spend $200M/year on cybertools Part of a new monster funding stream by NSF ($1B/year)

By MikeCarlo
(150 views)

GFS: The Google File System

GFS: The Google File System

GFS: The Google File System. Brad Karp UCL Computer Science. CS Z03 / 4030 30 th October, 2006. Motivating Application: Google. Crawl the whole web Store it all on “one big disk” Process users’ searches on “one big CPU” More storage, CPU required than one PC can offer

By maalik
(2 views)

Quiz Chapter 13, Brief Assessment Instruments

Quiz Chapter 13, Brief Assessment Instruments

Quiz Chapter 13, Brief Assessment Instruments. The Handbook of Psychological Assessment 5 th edition. 1. One of the main reasons for the increasing demand for brief instruments is: (519). Theoretical advances concern for patient welfare cost containment political correctness

By channing
(163 views)

Developing Chronic Disease Therapies Presentation to the FDA Science Board

Developing Chronic Disease Therapies Presentation to the FDA Science Board

Developing Chronic Disease Therapies Presentation to the FDA Science Board. Robert M Califf MD Director Duke Clinical Research Institute Details in: Health Affairs: 23:77-88; 2004. Key Points. Chronic diseases will be (are) the dominant health issue in our society

By eben
(2 views)

15-446 Distributed Systems Spring 2009

15-446 Distributed Systems Spring 2009

15-446 Distributed Systems Spring 2009. L-25 Cluster Computing. Overview. Google File System MapReduce BigTable. Google Disk Farm. Early days…. …today. Google Platform Characteristics. Lots of cheap PCs, each with disk and CPU High aggregate storage capacity

By lowri
(65 views)

Electric Power Analytics Consortium Meeting with Centerpoint , LLC Hurricane Planning and Big Data Analysis

Electric Power Analytics Consortium Meeting with Centerpoint , LLC Hurricane Planning and Big Data Analysis

Electric Power Analytics Consortium. Department of Electrical and Computer Engineering. July 18 th , 2013. Electric Power Analytics Consortium Meeting with Centerpoint , LLC Hurricane Planning and Big Data Analysis . Agenda. Overview on human resources

By charla
(110 views)

Research at Department of Computer and Systems Sciences – DSV

Research at Department of Computer and Systems Sciences – DSV

Research at Department of Computer and Systems Sciences – DSV. Key figures 2013. Full professors: 15 Visiting professors: 7 Senior lecturers: 31 Doctoral students: 95 of which are 26 female Licentiate Degrees awarded: 2 Doctoral Degrees awarded: 8 Research publications

By sumi
(70 views)

Overview of Data Mining and the KDD Process

Overview of Data Mining and the KDD Process

Overview of Data Mining and the KDD Process. Bamshad Mobasher DePaul University. From Data to Wisdom. Data The raw material of information Information Data organized and presented by someone Knowledge Information read, heard or seen and understood and integrated Wisdom

By maisie
(228 views)

Combining Statistics, Sampling, and Indexing to Quantitatively Scale Massive Scientific Data

Combining Statistics, Sampling, and Indexing to Quantitatively Scale Massive Scientific Data

Combining Statistics, Sampling, and Indexing to Quantitatively Scale Massive Scientific Data. Science Problem: Climate and cosmological analysis and exploration via queries on their massive data sets may still result in a massive amount of data for the scientist to comb through and/or transfer.

By garan
(92 views)

Grant Writing 101

Grant Writing 101

Grant Writing 101. Presented by: Carla Borden, Research Development Specialist Rebekah Craig, Research Development Specialist. Today’s Objectives. Basic Components Writing for Review Problem Statement / Specific Aims Narrative. Basic Components. Standard Proposal Content.

By ember
(152 views)

The Structure of Networks

The Structure of Networks

The Structure of Networks. with emphasis on information and social networks. T-214-SINE Summer 2011 Chapter 2 Ýmir Vigfússon. Graph theory. We will develop some basics of graph theory This provides a unifying language for network structure We begin with central definitions

By monet
(132 views)

C11- Managing Knowledge

C11- Managing Knowledge

C11- Managing Knowledge. About Knowledge . Knowledge is a firm asset: . Data: Flow of events or transactions captured by organization’s systems Knowledge: Cognitive event in people's heads; know how; situational Knowledge Management:

By tybalt
(273 views)

Teradata Columnar: A new standard for Columnar databases

Teradata Columnar: A new standard for Columnar databases

Teradata Columnar: A new standard for Columnar databases. Source: Teradata is thinking Big Stephen Swoyer Presented by: Deesha Phalak and Kaushiki Nag. Summary. Teradata Corporation introduced Teradata Columnar that integrates columnar and row-based tables.

By shepry
(310 views)

Big Data Overview of storage and processing

Big Data Overview of storage and processing

Big Data Overview of storage and processing. David Gibbs and Govardhan Tanniru Georgia State University Department of Computer Science P.O. Box 3965 Atlanta, GA 30302-3965. . Big Data. Big Data does not only relate to the size of data

By liliha
(128 views)

Iyad Obeid PhD, Joseph Picone PhD

Iyad Obeid PhD, Joseph Picone PhD

Accelerating the Rate of Technology Development in Neural Engineering Through a Common Evaluation Paradigm. PI. PI. PI. Data. Data. Data. Methods. Methods. Methods. Results. Results. Results. Iyad Obeid PhD, Joseph Picone PhD. Research Question. Research Question. Research Question.

By tal
(176 views)

Coherency Sensitive Hashing (CSH)

Coherency Sensitive Hashing (CSH)

Coherency Sensitive Hashing (CSH). Simon Korman and Shai Avidan Dept. of Electrical Engineering Tel Aviv University ICCV2011 | 13th International Conference on Computer Vision. Outline. Introduction Locality Sensitive Hashing for Finding Nearest Neighbors

By senona
(308 views)

Massively Parallel Astronomic Event Detection u sing GPU’s

Massively Parallel Astronomic Event Detection u sing GPU’s

Massively Parallel Astronomic Event Detection u sing GPU’s. Matthias Alexander Lee Wentworth Institute of Technology Dr. Pavlos Protopapas Help and Moral support: Richard Edgar, Mike Clark and Tom Buckley. What are we detecting?. Trans-Neptunian-Objects Light Curves

By onslow
(111 views)

July 2012 Update July 12, 2012 Andrew J. Buckler, MS Principal Investigator, QI-Bench

July 2012 Update July 12, 2012 Andrew J. Buckler, MS Principal Investigator, QI-Bench

July 2012 Update July 12, 2012 Andrew J. Buckler, MS Principal Investigator, QI-Bench. With Funding Support provided by National Institute of Standards and Technology. Agenda for Today. Approach, plans , and progress on Testing Analysis Modules Overview Bias- Linearity Demo

By job
(149 views)

VACET: Deploying Technology for Visualizing and Analyzing Astrophysics Simulations

VACET: Deploying Technology for Visualizing and Analyzing Astrophysics Simulations

VACET: Deploying Technology for Visualizing and Analyzing Astrophysics Simulations. Author May 19, 2009. Outline VACET Overview VisIt Overview Success stories with CAC Parallel particle advection (streamlines) Topology. Director’s Review of CRD | August 24 - 26, 2009. Outline

By feryal
(125 views)

Efficient Detection of Empty Result Queries

Efficient Detection of Empty Result Queries

Efficient Detection of Empty Result Queries. Gang Luo IBM T.J. Watson Research Center luog@us.ibm.com. Empty Result Problem. Query returns an empty result set User gets lost about where to look at next Frequently encountered in interactive exploration of massive data sets

By december
(128 views)

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