Demo Data from EDBT 2026 / reviewers in the wild / expert
Timothy K. Paine
dblp:142/3197
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
0009-0001-9819-9972ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Software engineering, systems software and programming languages · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Database system architecture and tuning · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware accelerators and domain-specific architectures · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware accelerators and domain-specific architectures
database accelerator |
0.2 | 1 | 2014 | Q100: the architecture and design of a database processing unit · ASPLOS 2014 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.4coarse-grained instruction · 0.4ASIC tile · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Q100: the architecture and design of a database processing unitabstractIn this paper, we propose Database Processing Units, or DPUs, a class of domain-specific database processors that can efficiently handle database applications. As a proof of concept, we present the instruction set architecture, microarchitecture, and hardware implementation of one DPU, called Q100. The Q100 has a collection of heterogeneous ASIC tiles that process relational tables and columns quickly and energy-efficiently. The architecture uses coarse grained in- structions that manipulate streams of data, thereby maximizing pipeline and data parallelism, and minimizing the need to time multiplex the accelerator tiles and spill inter- mediate results to memory. This work explores a Q100 de- sign space of 150 configurations, selecting three for further analysis: a small, power-conscious implementation, a high- performance implementation, and a balanced design that maximizes performance per Watt. We then demonstrate that the power-conscious Q100 handles the TPC-H queries with three orders of magnitude less energy than a state of the art software DBMS, while the performance-oriented design out- performs the same DBMS by 70X. Lisa Wu Wills, Andrea Lottarini, Timothy K. Paine, Martha A. Kim, Kenneth A. Ross |
ASPLOS | 3 |