[Talks] Brown CS Seminar: Ailamaki talk in Lubrano on 3/20/2000 at 12:00 pm

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			       CS Seminar
		   The Department of Computer Science
			    BROWN UNIVERSITY

			        presents

			    Anastassia Ailamaki 


		    Monday, March 20, 2000 at 12:00 PM

	          Lubrano Conference Room (CIT 4th floor)

	          Refreshments will be served at 11:45 AM

                ``Architecture-conscious Database Systems''



			       Abstract

Modern high-performance processors employ sophisticated techniques to
overlap and simultaneously execute multiple computation and memory
operations. Intuitively, these techniques should help database
applications, which are becoming increasingly compute and memory bound.
Unfortunately, recent research indicates that, unlike scientific
workloads, database systems' performance has not improved 
commensurately with increases in processor speeds. As the gap 
between memory and processor speed widens, research on database 
systems has focused on minimizing memory latencies for isolated 
algorithms. However, in order to design high-performance database 
systems it is important to carefully evaluate and understand the 
interaction between the database software and the underlying hardware. 

The first part of this talk introduces a framework for analyzing query
execution time on a database system running on a server with a modern
processor and memory architecture. Experiments with a variety of
benchmarks show that database developers should (a) optimize data
placement for the second level of data cache, (b) optimize instruction
placement to reduce first-level instruction cache stalls, but (c) not
expect the overall execution time to decrease significantly without
addressing stalls related to subtle implementation issues (e.g., branch
prediction).

The second part of the talk focuses on optimizing data placement for
access to the second-level cache. Most commercial DBMSs store records
contiguously on disk pages, using the slotted-page approach (NSM).
During single attribute scan, NSM exhibits poor spatial locality and has
a negative impact on cache performance. The decomposition storage model
(DSM) has better spatial locality, but incurs a high record
reconstruction cost. We introduce Page-level Attribute Grouping (PAG), a
new layout for data records that is applied orthogonally to NSM pages
and offers optimized cache utilization with no extra space or time
penalty.


		 Host: Professor Steve Reiss