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1 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Convergence of HPC, Databases, and Analytics Tirthankar Lahiri Senior Director, Oracle TimesTen In-Memory Database
2 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Real-Time Analytics Social Media Telecommunications Enabling The Real-Time World eCommerce Multicore 64-bit Processors Massive DRAM capacity High-Speed Networks Financial Services Next Generation DBMSs SSD/Persistent Memory
3 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Analytics Requirements Intuitive interfaces Instantaneous response time Real-time reporting Structured / Unstructured data Extreme concurrency
4 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Hardware Trends Processor throughput –Cores per socket: 5x in last 5 years –Clock frequency: Flat in last 2 years Memory capacity 2x every 2 years High-speed networking: Infiniband, RapidIO, 10GigE, etc. Persistent memory technologies –Flash replacing disks for online storage –PC-RAM, MRAM : extension of RAM, or superfast disks for hot data
5 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Database Design Trends Emerging Industry Trend Exadata, Exalytics, Big-Data Appliance Balanced Compute/Capacity/Power Co-developed components Built-in scale up, scale out Built-in interoperability Pushdown functionality into hardware Exadata Smart Storage Integrated Appliances
6 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. In-Memory Analytics Software Memory Optimized Essbase TimesTen for Exalytics Adaptive In-Memory Tools 1 TB RAM 40 Processing Cores High Speed Networking In-Memory Analytics Hardware Optimized Oracle Business Intelligence Foundation Suite Example: Oracle Exalytics In-Memory Machine
7 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Database Design Trends CPU core performance is flat Parallelize (dont paralyze) –Coarse-grained parallelism Exploit workload parallelism Parallelize query execution Parallelize maintenance operations (backup/restore) Exploit high speed communication primitives (e.g. Infiniband RDS ) –Fine-grained parallelism Vector execution Multi-threading of low-level primitives Parallelism Everywhere
8 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Database Design Trends Use all the available tools: –In-memory storage when applicable –Column storage for sequential accesses –Row storage for random accesses Advanced compression techniques –More bang for your storage buck !! Beware of NUMA !! –NUMA locality awareness –Lock free or well partitioned data structures –Avoid global updates to shared memory Storage Management
9 Copyright © 2012 Oracle and/or its affiliates. All rights reserved. Database Design Trends Enhance for analytics Analytic functions, data mining models, graph models, etc Cache-friendly access methods Sequential scans better than random access Cost modeling for modern hardware –Disk IOs are no longer the dominant cost –Cache Misses / Memory References –CPU cycles, execution time Query Optimization Wheres that plan??
10 Copyright © 2012 Oracle and/or its affiliates. All rights reserved.
Oracle Exalytics Business Intelligence Machine Eshaanan Gounden – Core Technology Team.
Copyright © 2012, Oracle and/or its affiliates. All rights reserved. 1.
WHAT EXACTLY IS ORACLE EXALYTICS?. 2 What Exactly Is Exalytics? AGENDA Exalytics At A Glance The Exa Family Do We Need Exalytics? Hardware & Software.
Looking Forward while Looking Backwards Essbase and Exalytics Seldon Goodwin Principal Sales Consultant Oracle Business Intelligence.
Oracle Exadata for SAP.
Next Generation Operating Systems Zeljko Susnjar, Cisco CTG June 2015.
Extreme Performance with Oracle Data Warehousing Andreas Katsaris Data warehouse and BI Practice Manager, Arisant LLC.
Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 1 Preview of Oracle Database 12 c In-Memory Option Thomas Kyte
10 REASONS Why it makes a good option for your DB IN-MEMORY DATABASES Presenter #10: Robert Vitolo.
Introduction to Data Analysis with R on HPC Texas Advanced Computing Center Feb
Technische Universität München Massively Parallel Sort-Merge Joins (MPSM) in Main Memory Multi-Core Database Systems Martina Albutiu, Alfons Kemper, and.
Oracle Confidential – Highly Restricted1. Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Safe Harbor Statement The following is.
Exadata Distinctives Brown Bag New features for tuning Oracle database applications.
Oracle Data Warehouse Strategic Update Ray Roccaforte.
Copyright © 2012, Oracle and/or its affiliates. All rights reserved. 1 Oracle on Oracle Harry Corcell - Hardware Account Manager Samin Sabetazad - Technical.
Data Warehousing 1 Lecture-24 Need for Speed: Parallelism Virtual University of Pakistan Ahsan Abdullah Assoc. Prof. & Head Center for Agro-Informatics.
Data Mining with R/ORE Minming Duan. 2 iTech Solution Profile Agenda R/ORE Overview 1 XML output generation using SQL 4 Integration with IBP and BIEE.
VVols with Adaptive Flash and InfoSight Analytics 1 Manchester Virtualisation User Group Rich Fenton (Nimble North Senior Systems Engineer)
Introduction to Exadata X5 and X6 New Features Michael MessinaSridhar Avantsa Senior Managing ConsultantAssociate Practice DirectorRolta-AdvizeX
Inside the Exalytics Osama Mustafa Gurus Solutions.
1. Aim High with Oracle Real World Performance Andrew Holdsworth Director Real World Performance Group Server Technologies.
Hardware Architecture. Computing Infrastructure Components Components Servers Clients LAN & WLAN Internet Connectivity Software Storage Backup Security.
Copyright © 2012, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 12 1.
Removing the I/O Bottleneck with Virident PCIe Solid State Storage Solutions Jan Silverman VP Operations.
Parallel IO for Cluster Computing Tran, Van Hoai.
Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 1.
Course Introduction Andy Wang COP 5611 Advanced Operating Systems.
Copyright © 2006, GemStone Systems Inc. All Rights Reserved. Increasing computation throughput with Grid Data Caching Jags Ramnarayan Chief Architect GemStone.
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any.
Introduction. Outline What is database tuning What is changing The trends that impact database systems and their applications What is NOT changing The.
Comp-TIA Standards. AMD- (Advanced Micro Devices) An American multinational semiconductor company that develops computer processors and related technologies.
Fast Data at Massive Scale Lessons Learned at Facebook Bobby Johnson.
Meanwhile RAM cost continues to drop Moore’s Law on total CPU processing power holds but in parallel processing… CPU clock rate stalled… Because.
1 Some Context for This Session… Performance historically a concern for virtualized applications By 2009, VMware (through vSphere) and hardware vendors.
COMPUTER ORGANIZATIONS CSNB123. COMPUTER ORGANIZATIONS CSNB123 Why do you need to study computer organization and architecture? Computer science and IT.
The Sun Oracle Database Machine Barry Hodges Senior Solution Architect Oracle New Zealand.
Oracle’s Big Plans For Big Data Analysis By Doug Henschen, InformationWeek, Oct 4 th, 2011 Presented by Group 7: Sam Tucker and Ayoung Noh.
Impact of the convergence of three worlds: High-Performance Computing, Databases, and Analytics Stefan Manegold
Hardware Trends. Contents Memory Hard Disks Processors Network Accessories Future.
Database Storage by Oracle. StorageTek Tape HelpfulHarmful Internal StrenghsWeakness Fast sequential data transfers More compact and lighter wieght than.
1 HYRISE – A Main Memory Hybrid Storage Engine By: Martin Grund, Jens Krüger, Hasso Plattner, Alexander Zeier, Philippe Cudre-Mauroux, Samuel Madden, VLDB.
Performance and Scalability. Performance and Scalability Challenges Optimizing PerformanceScaling UpScaling Out.
Infrastructure for Data Warehouses. Basics Of Data Access Data Store Machine Memory Buffer Memory Cache Data Store Buffer Bus Structure.
Antoine Chambille Head of Research & Development, Quartet Amir Javanshir Principal Software Engineer,
U NIVERSITY U NIVERSITY OF T ORONTO U NIVERSITY OF T ORONTO Bionic databases are coming. What will they look like? *Ryan Johnson & Ippokratis Pandis**
1 Advanced Storage Technologies for High Performance Computing Sorin, Faibish EMC NAS Senior Technologist IDC HPC User Forum, April 14-16, Norfolk, VA.
Your Data Any Place, Any Time Performance and Scalability.
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