DaMoN 2014 - Tenth International Workshop on Data Management on New Hardware

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. Multi-core CPUs, GPUs, new memory and storage technologies (such as flash and phase change memory), and low-power hardware 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 passing maximum performance to applications in transparent fashion. 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
novel application of new storage technologies (flash, PCM, etc.) to data management
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
.: Workshop Co-Chairs
Alfons Kemper, TU-München (kemper-AT-in.tum.de)
Ippokratis Pandis, IBM Research - Almaden (ipandis-AT-us.ibm.com)
.: Program Committee
Stratos Idreos, Harvard
Martin Kersten, CWI
Hideaki Kimura, HP Labs
Wolfgang Lehner, TU Dresden
Qiong Luo, HKUST
Rene Mueller, IBM Research - Almaden
Jignesh Patel, University of Wisconsin - Madison
Eric Sedlar, Oracle Labs
Rusty Sears, Microsoft CISL
Jens Teubner, TU Dortmund