Dissertation
Performance modelling and high performance buffer design for the system with network on chip
Washington State University
Doctor of Philosophy (PhD), Washington State University
12/2007
DOI:
https://doi.org/10.7273/000005748
Abstract
High performance novel dynamically allocated multi-queue (DAMQ) buffer schemes for
systems with network on chip (NoC) have been proposed and evaluated in this dissertation. An
analytical model to predict performance of a NoC where wormhole switching technique and
fully adaptive routing protocols has been developed and compared with simulations.
In this dissertation, a novel analytical model for NoC which makes use of simple close
form calculations is presented. This model provides accurate network performance prediction in
the network stable region. The validity of this model is demonstrated by comparing analytical
prediction with simulation results obtained on high-radix k-ary 2-cube networks.
Three novel switch buffer schemes, DAMQall, DAMQmin and DAMQshared, for system on
chip with an interconnection network are also reported. The proposed schemes are based on a
DAMQ self-compacting buffer hardware design. These schemes outperform existing approaches.
DAMQall have similar performance using only half of the buffer size used in traditional SAMQ
implementations. DAMQmin provides an excellent approach to optimize buffer management
providing a good throughput when the network has a larger load. DAMQshared scheme lets virtual
channels from different physical channel share free buffer space. While providing similar
performance, DAMQshared scheme uses only around sixty percent of the buffer size that is used in
traditional implementation for NoCs. In addition, using same size buffers, DAMQshared
outperforms existing approaches such as SAMQ and DAMQall by 1% to 2% in throughput. The
proposed schemes also make a better utilization of the available buffer space.
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Details
- Title
- Performance modelling and high performance buffer design for the system with network on chip
- Creators
- Jin Liu
- Contributors
- Jose G Delgado-Frias (Chair) - Washington State University, School of Electrical Engineering and Computer ScienceKung-Chi Wang (Committee Member) - Washington State University, School of Electrical Engineering and Computer ScienceSirisha Medidi (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- School of Electrical Engineering and Computer Science
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Publisher
- Washington State University
- Number of pages
- 125
- Identifiers
- 99901054761901842
- Language
- English
- Resource Type
- Dissertation