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Multicore Systems On-Chip: Practical Software/Hardware Design (Hardcover, 2nd Revised edition)
Loot Price: R2,109
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Multicore Systems On-Chip: Practical Software/Hardware Design (Hardcover, 2nd Revised edition)
Series: Atlantis Ambient and Pervasive Intelligence, 7
Expected to ship within 12 - 17 working days
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System on chips designs have evolved from fairly simple unicore,
single memory designs to complex heterogeneous multicore SoC
architectures consisting of a large number of IP blocks on the same
silicon. To meet high computational demands posed by latest
consumer electronic devices, most current systems are based on such
paradigm, which represents a real revolution in many aspects in
computing. The attraction of multicore processing for power
reduction is compelling. By splitting a set of tasks among multiple
processor cores, the operating frequency necessary for each core
can be reduced, allowing to reduce the voltage on each core.
Because dynamic power is proportional to the frequency and to the
square of the voltage, we get a big gain, even though we may have
more cores running. As more and more cores are integrated into
these designs to share the ever increasing processing load, the
main challenges lie in efficient memory hierarchy, scalable system
interconnect, new programming paradigms, and efficient integration
methodology for connecting such heterogeneous cores into a single
system capable of leveraging their individual flexibility. Current
design methods tend toward mixed HW/SW co-designs targeting
multicore systems on-chip for specific applications. To decide on
the lowest cost mix of cores, designers must iteratively map the
device's functionality to a particular HW/SW partition and target
architectures. In addition, to connect the heterogeneous cores, the
architecture requires high performance complex communication
architectures and efficient communication protocols, such as
hierarchical bus, point-to-point connection, or Network-on-Chip.
Software development also becomes far more complex due to the
difficulties in breaking a single processing task into multiple
parts that can be processed separately and then reassembled later.
This reflects the fact that certain processor jobs cannot be easily
parallelized to run concurrently on multiple processing cores and
that load balancing between processing cores - especially
heterogeneous cores - is very difficult.
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