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This book introduces a generic and systematic design-time/run-time
methodology for handling the dynamic nature of modern embedded
systems, without adding large safety margins in the design. The
techniques introduced can be utilized on top of most existing
static mapping methodologies to deal effectively with dynamism and
to increase drastically their efficiency. This methodology is based
on the concept of system scenarios, which group system behaviors
that are similar from a multi-dimensional cost perspective, such as
resource requirements, delay, and energy consumption. Readers will
be enabled to design systems capable to adapt to current inputs,
improving system quality and/or reducing cost, possibly learning
on-the-fly during execution. Provides an effective solution to deal
with dynamic system design Includes a broad survey of the
state-of-the-art approaches in this domain Enables readers to
design for substantial cost improvements (e.g. energy reductions),
by exploiting system scenarios Demonstrates how the methodology has
been applied effectively on various, real design problems in the
embedded system context
This book introduces a generic and systematic design-time/run-time
methodology for handling the dynamic nature of modern embedded
systems, without adding large safety margins in the design. The
techniques introduced can be utilized on top of most existing
static mapping methodologies to deal effectively with dynamism and
to increase drastically their efficiency. This methodology is based
on the concept of system scenarios, which group system behaviors
that are similar from a multi-dimensional cost perspective, such as
resource requirements, delay, and energy consumption. Readers will
be enabled to design systems capable to adapt to current inputs,
improving system quality and/or reducing cost, possibly learning
on-the-fly during execution. Provides an effective solution to deal
with dynamic system design Includes a broad survey of the
state-of-the-art approaches in this domain Enables readers to
design for substantial cost improvements (e.g. energy reductions),
by exploiting system scenarios Demonstrates how the methodology has
been applied effectively on various, real design problems in the
embedded system context
Data Access and Storage Management for Embedded Programmable
Processors gives an overview of the state-of-the-art in
system-level data access and storage management for embedded
programmable processors. The targeted application domain covers
complex embedded real-time multi-media and communication
applications. Many of these applications are data-dominated in the
sense that their cost related aspects, namely power consumption and
footprint are heavily influenced (if not dominated) by the data
access and storage aspects. The material is mainly based on
research at IMEC in this area in the period 1996-2001. In order to
deal with the stringent timing requirements and the data dominated
characteristics of this domain, we have adopted a target
architecture style that is compatible with modern embedded
processors, and we have developed a systematic step-wise
methodology to make the exploration and optimization of such
applications feasible in a source-to-source precompilation
approach.
Data Access and Storage Management for Embedded Programmable
Processors gives an overview of the state-of-the-art in
system-level data access and storage management for embedded
programmable processors. The targeted application domain covers
complex embedded real-time multi-media and communication
applications. Many of these applications are data-dominated in the
sense that their cost related aspects, namely power consumption and
footprint are heavily influenced (if not dominated) by the data
access and storage aspects. The material is mainly based on
research at IMEC in this area in the period 1996-2001. In order to
deal with the stringent timing requirements and the data dominated
characteristics of this domain, we have adopted a target
architecture style that is compatible with modern embedded
processors, and we have developed a systematic step-wise
methodology to make the exploration and optimization of such
applications feasible in a source-to-source precompilation
approach.
In a first part of the book, we introduce the context and
motivation, followed by a once-over-lightly view of the entire
approach, illustrated on a relevant driver from the targeted
application domain. In part 2, we show how source-to-source code
transformations play a crucial role in the solution of the earlier
mentioned data transfer and storage bottleneck in modern processor
architectures for multi-media and telecommunication applications.
This is especially true for embedded applications where cost issues
like memory footprint and power consumption are vital. It is also
shown that many of these code transformations can be defined in a
platform-independent way. The resulting optimized code behaves
betteron any of the modern platforms. The steps include global
data-flow and loop transformations, data reuse decisions,
high-level estimators and the link with parallelisation and
multi-processor partitioning. In part 3 we discuss our research
efforts relating to the mapping of embedded applications to
specific memory organisations in embedded programmable processors.
In a traditional processor-based environment, compilers perform
memory optimizations assuming a fully fixed hardware target
architecture with only maximal performance in mind. However, in an
embedded context also cost issues and especially power consumption
and memory footprint play a dominant role too. Usually the timing
requirements are given and the application designer is mostly
interested in the trade-off between timing characteristics of the
different application tasks and their cost effects. For this
purpose Pareto type trade-off curves are the most suitable vehicle
to address this design problem. The steps involved here include the
storage cycle budget distribution, support of modern memory
architectures like SDRAMs, and cache related issues.
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