ABSTRACT
With
the increase in the possibility of incorporating multiple cores on a single
chip (MCSoC), the issue of an efficient interconnection that is scalable, takes
up small area and has low power consumption must be taken into consideration
carefully. Network on chip (NoC) has evolved as a promising solution for
efficiently interconnecting multiple core on a single chip (MCSoC). NoC brings
conventional networking theories and methods to chip communication and brings notable
improvements over the conventional bus systems. The aim of my research will be
to study power consumption in NoC architecture and propose an effective
dynamic remapping algorithm to reduce power consumption on NoC. This is done
by monitoring the NoC at run time and dynamically re-mapping the cores to
reduce power consumption. Low power consumption is desirable in MCSoC because
high power increases capacitance, electro magnetic interference (EMI) and
dissipates more heat, thereby reducing performance. In addition, must devices
built using MCSoC are hand-held devices (battery powered) and therefore might
not have access to continuous power supply. I will be using the OASIS NoC which
was developed at the Adaptive systems laboratory, The University of Aizu,
Graduate School of Computer Science and Engineering. Aizu, Japan To test my
Algorithm. OASIS NoC is a complexity effective on-chip interconnection
network.
Chapter
I
1.0 Introduction
For
the next decade, Moore’s Law is still going to bring higher transistor
densities allowing billions of transistors to be integrated on a single chip.
However, it became obvious that exploiting significant amounts of
instruction-level parallelism with deeper pipelines and more aggressive wide-issue
super-scalar techniques, and using most of the transistor budget for large
on-chip caches has come to a dead end. Scaling performance with higher clock
frequencies, especially, is getting more and more difficult because of heat
dissipation problems and energy consumption that is too high. The latter is not
only a technical problem for mobile systems, but is also becoming a severe problem
for computing centres because high energy consumption leads to significant cost
factors in the budget. Improving performance can only be achieved by exploiting
parallelism on all system levels [1]. Multicore architectures offer a better
performance/Watt ratio than single-core architectures with similar performance.
Combining multi-core and co-processor technology promise extreme computing
power for high CPU-time-consuming applications. [1]
Department: Computer Science (M.Sc Thesis)
Format: MS Word
Chapters: 1 - 5, Preliminary Pages, Abstract, References, Appendix.
No. of Pages: 66
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