VLDB 2026 Research / reviewers in the wild / expert
Gadi Oxman
dblp:39/10928
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2016
0000-0001-5612-1897ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-author
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 |
Interconnection networks and networks-on-chip · 81% Performance modeling and evaluation · 19% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interconnection networks and networks-on-chip › routing algorithms
deflection routing |
0.2 | 1 | 2016 | An NoC Simulator That Supports Deflection Routing, GPU/CPU Integration, and Co-Simulation · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2016 |
Interconnection networks and networks-on-chip
network-on-chip simulation |
0.1 | 1 | 2016 | An NoC Simulator That Supports Deflection Routing, GPU/CPU Integration, and Co-Simulation · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2016 |
Performance modeling and evaluation
simulation |
0.1 | 1 | 2016 | An NoC Simulator That Supports Deflection Routing, GPU/CPU Integration, and Co-Simulation · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2016 |
Methods — techniques the papers use, named apart from their topics
synthetic traffic generation · 0.2latency modeling · 0.2co-simulation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | An NoC Simulator That Supports Deflection Routing, GPU/CPU Integration, and Co-SimulationabstractWe present deflection routing network on chip simulator (DNOC), a network-on-chip simulator. DNOC is primarily a deflection routing simulator, it simulates custom network topologies with detailed deflection router models, and a basic virtual channel router. DNOC can generate various statistics, such as network latency and power. We evaluate the simulator in three typical use cases. In stand-alone simulation, synthetic traffic generators are used to offer load to the network. In synchronous co-simulation, the simulator is integrated as a module within a larger system simulator with synchronization every simulated cycle. In the faster model-based co-simulation mode, a latency model is built, and retuned periodically at longer time intervals. We demonstrate co-simulation by running applications from the Rodinia and SPLASH-2 benchmark sets on mesh variants. DNOC is also able to run on multicore processors, speeding up the simulation of large networks. Gadi Oxman, Shlomo Weiss |
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. | 1 |
| 2015 | DNOC: an accurate and fast virtual channel and deflection routing network-on-chip simulatorabstractWe present DNOC, a network-on-chip simulator. DNOC simulates custom network topologies with detailed router models. Both classic virtual channel (VC) based router models and deflection routing models are supported. We validate the simulation models against hardware RTL router models. DNOC can generate various statistics, such as network latency and power. We evaluate the simulator in three typical use cases. In stand-alone simulation, synthetic traffic generators are used to offer load to the network. In synchronous co-simulation, the simulator is integrated as a module within a larger system simulator with synchronization every simulated cycle. In the faster model based co-simulation mode, a latency model is built, and re-tuned periodically at longer time intervals. We demonstrate co-simulation by running applications from the Rodinia and SPLASH-2 benchmark sets on mesh variants. DNOC is also able to run on multiple x86 cores in parallel, speeding up the simulation of large networks. Gadi Oxman, Shlomo Weiss |
ISPASS | 1 |