high performance embedded computing © 2007 elsevier chapter 1, part 2: embedded computing high...
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High Performance Embedded Computing
© 2007 Elsevier
Chapter 1, part 2: Embedded Computing
High Performance Embedded ComputingWayne Wolf
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© 2006 Elsevier
Topics
Design methodologies. Methodologies and standards.
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Design goals
Functional requirements: input/output relations.
Non-functional requirements: cost, performance, power, etc.
Some project goals may be difficult to measure.
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Aspects of performance
Embedded system performance can be measured in many ways: Average vs. worst/best-case. Throughput vs. latency. Peak vs. sustained.
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Energy/power
Energy consumption is important for battery life.
Power consumption is important for heat generation or for generator-powered systems (vehicles).
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Cost
Manufacturing cost must be paid off across all the systems. Hardest in small-volume applications.
Manufacturing cost is incurred for each device.
Lifetime costs include software and hardware maintenance and upgrades.
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Other design attributes
Design time must be reasonable. May need to finish by a certain date.
System must be reliability; reliability requirements differ widely.
Quality includes reliability and other aspects: usability, durability, etc.
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Design methodology
Design methodology: a procedure for creating an implementation from a set of requirements.
Methodology is important in embedded computing: Must design many different systems. We may use same/similar components in many
different designs. Design time, results must be predictable.
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Embedded system design challenges Design space is large and irregular. We don’t have synthesis tools for many
steps. Can’t simulate everything. May need to build special-purpose simulators
quickly. Often need to start software development
before hardware is finished.
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Design complexity vs. designer productivity
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Basic design methodologies
Figure out flow of decision-making. Determine when bottom-up information is
generated. Determine when top-down decisions are
made.
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Waterfall and spiral models
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Hardware design flow
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Modeling in hardware
Technology databases capture manufacturing process information.
Cell libraries describe the cells used to compose designs.
Logic synthesis systems use routability and timing models.
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Hardware/software co-design flow
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Platform-based design
Platform includes hardware, supporting software.
Two stage process: Design the platform. Use the platform.
Platform can be reused to host many different systems.
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Platform design
Turn system requirements and software models into detailed requirements. Use profiling and analysis tools to measure
existing executable specifications. Explore the design space manually or
automatically. Optimize the system architecture based on
the results of simulation and other steps. Develop hardware abstraction layers and
other software.
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Programming platforms
Programming environment must be customized to the platform: Multiple CPUs. Specialized memory. Specialized I/O devices.
Libraries are often used to glue together processors on platforms.
Debugging environments are a particular challenge.
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Design verification and validation Testing exercises an implementation by
supplying inputs and testing outputs. Validation compares the implementation to a
specification or requirements. Verification may be performed at any design
stage; compares design at one level of abstraction to another.
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Design verification techniques Simulation uses an executable model, relies
on inputs. Formal methods generate a (possibly
specialized) proof. Manual methods, such as design reviews,
catch design errors informally.
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A methodology of methodologies Embedded systems include both hardware
and software. HW, SW have their own design methodologies.
Embedded system methodologies control the overall process, HW/SW integration, etc. Must take into account the good and bad points of
hardware and software design methodologies used.
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Useful methodologies
Software performance analysis. Architectural optimization. Hardware/software co-design. Network design. Software verification. Software tool generation.
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Joint algorithm and architecture development Some algorithm design is necessarily
performed before platform design. Algorithm development can be informed by
platform architecture design. Performance/power/cost trade-offs. Design trends over several generations.