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Architectural Support for Efficient Communication in Future Microprocessors

Traditionally, the microprocessor design has focused on the computational aspects
of the problem at hand. However, as the number of components on a single chip
continues to increase, the design of communication architecture has become a crucial
and dominating factor in defining performance models of the overall system. On-chip
networks, also known as Networks-on-Chip (NoC), emerged recently as a promising
architecture to coordinate chip-wide communication.
Although there are numerous interconnection network studies in an inter-chip
environment, an intra-chip network design poses a number of substantial challenges
to this well-established interconnection network field. This research investigates designs
and applications of on-chip interconnection network in next-generation microprocessors
for optimizing performance, power consumption, and area cost. First,
we present domain-specific NoC designs targeted to large-scale and wire-delay dominated
L2 cache systems. The domain-specifically designed interconnect shows 38%
performance improvement and uses only 12% of the mesh-based interconnect. Then,
we present a methodology of communication characterization in parallel programs
and application of characterization results to long-channel reconfiguration. Reconfigured
long channels suited to communication patterns enhance the latency of the
mesh network by 16% and 14% in 16-core and 64-core systems, respectively. Finally,
we discuss an adaptive data compression technique that builds a network-wide frequent value pattern map and reduces the packet size. In two examined multi-core
systems, cache traffic has 69% compressibility and shows high value sharing among
flows. Compression-enabled NoC improves the latency by up to 63% and saves energy
consumption by up to 12%.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-05-746
Date16 January 2010
CreatorsJin, Yu Ho
ContributorsKim, Eun Jung
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Dissertation
Formatapplication/pdf

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