DB system design for new hardware and sciences
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DB system design for new hardware and sciences
Anastasia Ailamaki
École Polytechnique Fédérale de Lausanneand
Carnegie Mellon University
introspective
parallelism
shar
ing
Uni-processor Multi-core
Multi-processor Cluster
Exploit max parallelism and sharing simultaneously
Moore’s Law = cores
Performance burden shifts to software
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1985 1990 1995 2000 2005 2010
Year of Introduction
Nu
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UltraSparc T2
Power4
80486
CRS-1 (Tensilica)
Multi-core challenges for DBMS
• CMP-aware parallelism in OLTP – Efficient synchronization– Highly concurrent algorithms
• CMP-aware sharing in BI– Eliminate redundancy with work sharing– Improve locality in query operators
• …
• But programmers are not multithreaded
sciences
Challenges: Complexity AND size
Alliez et al, INRIA, SIGGRAPH’05
Brain Mind Institute, EPFL
• Automate DB Design
• Computational Support
• Understanding Data
Summary
• Challenge #1: exploit hardware– Parallelism, sharing maximized simultaneously– Infrastructure to parallel thinking&programming
• Challenge #2: serve sciences– Reduce complexity through abstraction– Manage large datasets on large computers
“Multicore: This is the one which will have the biggest impact on us. We have never had a problem to solve like this. A breakthrough is needed in how applications are done on multicore devices.”
– Bill Gates
“It’s time we rethought some of the basics of computing. It’s scary and lots of fun at the same time.”
– Burton Smith