- Editors:
- Anastasia Ailamaki,
- Peter A. Boncz
Objective
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. CPUs with superscalar out-of-order execution, simultaneous multi-threading, multi-level memory hierarchies, and future storage hardware (such as flash drives) 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.
Paper Selection
The seven papers included in the workshop were chosen by the program committee from among sixteen high-quality submissions, following a review process in which each paper received at least three reviews. Based on the reviews, one paper was selected by the workshop chairs as the recipient of the "Best Paper" award. This year, the award goes to "Wimpy Node Clusters: What About Non-Wimpy Workloads?", by Willis Lang (University of Wisconsin); Jignesh M. Patel (University of Wisconsin); Srinath Shankar (Microsoft Corp.) .
Workshop Program
Eight technical papers were presented at the workshop. The workshop also featured a keynote talk by Evangelos Eleftheriou, IBM Fellow, IBM Zurich Lab. Additionally, the workshop included a panel on current challenges in cloud storage, moderated by Anastasia Ailamaki.
Proceeding Downloads
On the impact of flash SSDs on spatial indexing
Similarity queries are an important query type in multimedia databases. To implement these types of queries, database systems often use spatial index structures like the R*-Tree. However, the majority of performance evaluations for spatial index ...
Flashing databases: expectations and limitations
Flash devices (solid state disks) promise a significant performance improvement for disk-based database processing. However, database storage structures and processing strategies originally designed for magnetic disks prevent the optimal utilization of ...
Supporting extended precision on graphics processors
Scientific computing applications often require support for non-traditional data types, for example, numbers with a precision higher than 64-bit floats. As graphics processors, or GPUs, have emerged as a powerful accelerator for scientific computing, we ...
Optimizing read convoys in main-memory query processing
Concurrent read-only scans of memory-resident fact tables can form convoys, which generally help performance because cache misses are amortized over several members of the convoy. Nevertheless, we identify two performance hazards for such convoys. One ...
Fast integer compression using SIMD instructions
We study algorithms for efficient compression and decompression of a sequence of integers on modern hardware. Our focus is on universal codes in which the codeword length is a monotonically non-decreasing function of the uncompressed integer value; such ...
The effects of virtualization on main memory systems
Virtualization is mainly employed for increasing the utilization of a lightly-loaded system by consolidation, but also to ease the administration based on the possibility to rapidly provision or migrate virtual machines. These facilities are crucial for ...
Wimpy node clusters: what about non-wimpy workloads?
The high cost associated with powering servers has introduced new challenges in improving the energy efficiency of clusters running data processing jobs. Traditional high-performance servers are largely energy inefficient due to various factors such as ...