DaMoN 2016 - Twelfth International Workshop on Data Management on New Hardware (DaMoN 2016)

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.
.: Topics of Interest
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 Chairs
Anastasia Ailamaki, EPFL (anastasia.ailamaki-AT-epfl.ch)
Stratos Idreos, Harvard University (stratos-AT-seas.harvard.edu)
.: Program Committee
Gustavo Alonso, ETHZ
Cagri Balkesen, Oracle
Shimin Chen, Chinese Academy of Sciences
Hideaki Kimura, HP Labs
Sang Won Lee, Sungkyunkwan University, Korea
Wolfgang Lehner, TU Dresden
Justin Levandoski , Microsoft Research
Hiroki Matsutani, Keio University, Japan
Rene Mueller, IBM Research - Almaden
Ippokratis Pandis, Amazon Web Services
Jignesh Patel, University of Wisconson - Madison
Jens Teubner, TU Dortmund