Title
High performance network-on-chip simulation by interval-based timing predictions.
Abstract
Current multi- and many-core computer architectures heavily use Network-on-Chip (NoC communication in order to meet the increased bandwidth demands between the processors and for reasons of scalability. For the proper analysis of concurrency utilization, and workload distribution of parallel multi-media applications running on such NoC-based architectures, high-speed simulation techniques are required. Apart from accurate timing simulation of compute resources, it is of utmost importance also to accurately model the delays caused by the packet-based network communication in order to reliably verify performance numbers, or to identify any bottlenecks of the underlying architecture, or to study workload distribution techniques or routing algorithms. In this paper, we present a novel simulation approach for NoCs that allows to simulate such communication delays equally accurate but much faster in average than on a flit-by-flit basis. We propose novel algorithmic and analytical techniques that predict the transmission intervals dynamically based on the arrival of communication requests, actual congestion in the NoC, routing information, packet lengths, and other parameters. According to such predictions, the simulation time may in many cases be automatically advanced, thus reducing the number of events to process in the simulator to a large extent. The presented NoC simulation technique has been integrated into a system-level multi-core architecture simulator. Experiments in running parallel real-world and multi-media applications on a simulated scalable NoC architecture show that we are able to achieve speedups of three orders of magnitude compared to cycle-accurate NoC simulators, while preserving a timing accuracy of above 95%.
Year
Venue
Field
2017
ESTImedia
Computer architecture simulator,Computer science,Concurrency,Workload,High performance network,Network packet,Network on a chip,Real-time computing,Bandwidth (signal processing),Scalability
DocType
ISBN
Citations 
Conference
978-1-4503-5117-1
0
PageRank 
References 
Authors
0.34
16
3
Name
Order
Citations
PageRank
Sascha Roloff1304.14
Frank Hannig259575.66
Jürgen Teich32886273.54