DaMoN 2015 - Eleventh International Workshop on Data Management on New Hardware (DaMoN 2015)

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
Ippokratis Pandis, Cloudera (ippokratis-AT-cloudera.com)
Martin Kersten, CWI (Martin.Kersten-AT-cwi.nl)
.: Program Committee
Shimin Chen, Chinese Academy of Sciences
Bingsheng He, Nanyang Technological University
Ryan Johnson, University of Toronto
Hideaki Kimura, HP Labs
Sang-Won Lee, Sungkyunkwan University, Korea
Wolfgang Lehner, TU Dresden
Justin Levandoski , Microsoft Research
Eric Lo, Hong Kong Polytechnic University
Rene Mueller, IBM Research - Almaden
Jignesh Patel, University of Wisconsin - Madison
Holger Pirk, CWI/MIT
Jens Teubner, TU Dortmund