- June 14, 2009: The presentation schedule has been determined.
- May 15, 2009: List of accepted papers posted.
- Apr 16, 2009: the submission deadline was extended to
Wednesday April 22, 1:00pm PST (21:00 GMT).
- Apr 15, 2009: Prof. Maurice Herlihy will give a keynote talk at DaMoN'09.
- Nov 19, 2008: The web site is up.
The aim of this one-day workshop is to bring together researchers who are interested in optimizing database performance on modern computing infrastructure by designing new data management techniques and tools.
The continued evolution of computing hardware and infrastructure imposes new challenges and bottlenecks to program performance. As a result, traditional database architectures that focus solely on I/O optimization increasingly fail to utilize hardware resources efficiently. CPUs with superscalar out-of-order execution, simultaneous multi-threading, multi-level memory hierarchies, and future storage hardware (such as MEMS) impose a great challenge to optimizing database performance. Consequently, exploiting the characteristics of modern hardware has become an important topic of database systems research.
The goal is to make database systems adapt automatically to the sophisticated hardware characteristics, thus maximizing performance transparently to applications. To achieve this goal, the data management community needs interdisciplinary collaboration with computer architecture, compiler and operating systems researchers. This involves rethinking traditional data structures, query processing algorithms, and database software architectures to adapt to the advances in the underlying hardware infrastructure.
We seek submissions bridging the area of database systems to computer architecture, compilers, and operating systems. In particular, submissions covering topics from the following non-exclusive list are encouraged:
cost models and query optimization for novel hierarchical memory systems
hardware systems for query processing
data management using co-processors
query processing using computing power in storage systems
database architectures for low-power computing and embedded devices
database architectures on multi-threaded and chip multiprocessors
database performance analysis, algorithms, and data structures on modern hardware
databases and transactional memory systems
performance analysis of database workloads on modern hardware
compiler and operating systems advances to improve database performance
new benchmarks for microarchitectural evaluation of database workloads
