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Digital Processing Platform

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Digital Processing Platform Low power design and implementation of computation associated with protocols and fusion algorithms Low power micro-controller – PowerPoint PPT presentation

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Title: Digital Processing Platform


1
Digital Processing Platform
  • Low power design and implementation of
    computation associated with protocols and fusion
    algorithms
  • Low power micro-controller
  • Small size for compact integration
  • Enables adaptation of node behavior with changing
    requirements, environmental characteristics, and
    network state
  • Enables experimentation with different algorithms
    and protocols
  • Enables use of energy saving processor modes and
    associated operating system functionality
  • Development of streamlined software
    implementations
  • Highly memory-constrained software
    implementations are required due to size and
    energy constraints
  • Must handle streaming nature of input data
  • Leverage our previous work in synthesis of
    memory-efficient embedded software
    implementations
  • Employ formal programming models, and apply
    graph-theoretic analysis and optimization of
    program structure
  • Explore migration into ASIC or 3D-integrated
    system

2
Example of Software Structure
Receiver
No new data
Periodic wake-up
Sensor
Transmitter
No
Broadcast new data
Extract data
Need to update neighbors?
Yes
3
Protocol Set-up and System Configuration
  • Handshaking
  • Source channel coding
  • Integrate with transceiver to establish PLL
    timing
  • Establish error correction coding
  • Establish low-complexity decoding
  • Assign transmission power
  • Assign processing tasks to network nodes

4
System-level Optimization ExampleTask
Assignment Algorithms
  • Need to balance communication and computation
    throughout the network
  • Develop models of power consumption in network
    nodes and communication links
  • Develop task graph models of overall network
    functionality
  • Develop algorithms to embed task graph algorithm
    specifications into the network
  • Assign processing tasks to network nodes
  • Turn off idle nodes
  • Large design space
  • Explore evolutionary algorithms to optimize task
    graph embeddings

5
Evolutionary Algorithms
Decoding function
Genetic operators
Genotype space(Genetic representation)
G(t)
6
Digital Design Summary
  • Contributions
  • Low power, memory-constrained implementation
    techniques
  • Application-specific optimization of software and
    VLSI
  • Integrated optimization of protocols and system
    configuration
  • Selected Prior Work
  • N. K. Bambha, S. S. Bhattacharyya, J. Teich, and
    E. Zitzler. Systematic integration of
    parameterized local search in evolutionary
    algorithms. IEEE Transactions on Evolutionary
    Computation. To appear.
  • S. S. Bhattacharyya. Hardware/software
    co-synthesis of DSP systems. In Y. H. Hu, editor,
    Programmable Digital Signal Processors
    Architecture, Programming, and Applications,
    pages 333-378. Marcel Dekker, Inc., 2002.
  • P. K. Murthy and S. S. Bhattacharyya. Shared
    buffer implementations of signal processing
    systems using lifetime analysis techniques. IEEE
    Transactions on Computer-Aided Design of
    Integrated Circuits and Systems, 20(2)177-198,
    February 2001.
  • S. S. Bhattacharyya, R. Leupers, and P. Marwedel.
    Software synthesis and code generation for DSP.
    IEEE Transactions on Circuits and Systems --- II
    Analog and Digital Signal Processing,
    47(9)849-875, September 2000.
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