Title
Parallel probe based dynamic connection setup in TDM NoCs
Abstract
We propose a Time-Division Multiplexing (TDM) based connection oriented NoC with a novel double time-wheel router architecture combined with a run-time parallel probing setup method. In comparison with traditional TDM connection setup methods, our design has the following advantages: (1) it allocates paths and time slots at run-time; (2) it is fast with predictable and bounded setup latency; (3) it avoids additional resources (no auxiliary network or central processor to find and manage connections); (4) it is fully distributed and therefore it scales nicely with network size. Compared to a packet based setup method, our probe based design can reduce path setup delay by 81% and increase network load by 110% in an 8×8 mesh, while avoiding the auxiliary network. Compared to a centralized method, our solution can double the success rate, while eliminating the central resource for path setup and reducing the wire overhead. Synthesis results suggest that our design is faster and smaller than all comparable solutions.
Year
DOI
Venue
2014
10.7873/DATE.2014.252
DATE
Keywords
Field
DocType
tdm nocs,centralized method,run-time parallel probing setup method,network routing,probe based design,central processor,increase network load,network load,auxiliary network,circuit switching,tdm based connection oriented noc,path setup delay,bounded setup latency,time slot allocation,setup method,time-division multiplexing,network size,parallel probe,double time-wheel router architecture,path allocation,path setup,traditional tdm connection setup,network-on-chip,packet based setup method,dynamic connection setup,routing,time division multiplexing,hardware,network on chip,radiation detectors
Network size,Circuit switching,Latency (engineering),Computer science,Network packet,Network on a chip,Real-time computing,Multiplexing,Connection-oriented communication,Bounded function
Conference
ISSN
Citations 
PageRank 
1530-1591
6
0.50
References 
Authors
14
3
Name
Order
Citations
PageRank
Shaoteng Liu1323.58
Axel Jantsch21875169.83
Zhonghai Lu31063100.12