Demo Data from EDBT 2026 / reviewers in the wild / expert
Stefan Liesche
dblp:25/6781
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software 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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 50% Performance modeling and evaluation · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing
concurrent data structures |
0.0 | 1 | 2000 | Priority Queues and Sorting Methods for Parallel Simulation · IEEE Trans. Software Eng. 2000 |
Parallel and multicore computing › concurrent data structures
concurrent priority queue |
0.0 | 1 | 2000 | Priority Queues and Sorting Methods for Parallel Simulation · IEEE Trans. Software Eng. 2000 |
Performance modeling and evaluation › simulation
discrete-event simulation |
0.0 | 1 | 2000 | Priority Queues and Sorting Methods for Parallel Simulation · IEEE Trans. Software Eng. 2000 |
Performance modeling and evaluation › simulation › parallel and distributed simulation
parallel simulation |
0.0 | 1 | 2000 | Priority Queues and Sorting Methods for Parallel Simulation · IEEE Trans. Software Eng. 2000 |
Methods — techniques the papers use, named apart from their topics
distributed splay trees · 0.0distributed sorted lists · 0.0concurrent heap · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Priority Queues and Sorting Methods for Parallel SimulationabstractThe authors examine the design, implementation, and experimental analysis of parallel priority queues for device and network simulation. They consider: 1) distributed splay trees using MPI; 2) concurrent heaps using shared memory atomic locks; and 3) a new, more general concurrent data structure based on distributed sorted lists, designed to provide dynamically balanced work allocation and efficient use of shared memory resources. We evaluate performance for all three data structures on a Cray-TSESOO system at KFA-Julich. Our comparisons are based on simulations of single buffers and a 64/spl times/64 packet switch which supports multicasting. In all implementations, PEs monitor traffic at their preassigned input/output ports, while priority queue elements are distributed across the Cray-TBE virtual shared memory. Our experiments with up to 60000 packets and two to 64 PEs indicate that concurrent priority queues perform much better than distributed ones. Both concurrent implementations have comparable performance, while our new data structure uses less memory and has been further optimized. We also consider parallel simulation for symmetric networks by sorting integer conflict functions and implementing a packet indexing scheme. The optimized message passing network simulator can process /spl sim/500 K packet moves in one second, with an efficiency that exceeds /spl sim/50 percent for a few thousand packets on the Cray-T3E with 32 PEs. All developed data structures form a parallel library. Although our concurrent implementations use the Cray-TSE ShMem library, portability can be derived from Open-MP or MP1-2 standard libraries, which will provide support for one-way communication and shared memory lock mechanisms. Miltos D. Grammatikakis, Stefan Liesche |
IEEE Trans. Software Eng. | 2 |