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Digital Processing System. Shuvra S. Bhattacharyya Department of Electrical and Computer Engineering, and Institute for Advanced Computer Studies University of Maryland College Park MD 20742 [email protected] , (301)405-3638, http://www.ece.umd.edu/~ssb/ With Neil Goldsman and Babis Papadopoulis.

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digital processing system

Digital Processing System

Shuvra S. BhattacharyyaDepartment of Electrical and Computer Engineering, andInstitute for Advanced Computer Studies

University of MarylandCollege Park MD [email protected], (301)405-3638,http://www.ece.umd.edu/~ssb/

With Neil Goldsman and Babis Papadopoulis

Laboratory affilations: Digital Signal Processing Laboratory, VLSI Design Automation Laboratory, Embedded Systems Research Laboratory, Communications and Signal Processing Laboratory

digital processing platform
Digital Processing Platform
  • 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
    • 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
example of software structure
Low power sleep mode

Check for new data

Fuse with prior data

Example of Software Structure

Receiver

No new data

Periodic wake-up

Sensor

Transmitter

No

Broadcast new data

Extract data

Yes

Need to update neighbors?

protocol set up and system configuration
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
system level optimization example task assignment algorithms
System-level Optimization Example:Task 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
evolutionary algorithms
Selection

Phenotype space(Original search space)

P(t)

P(t+1)

G(t+1)

Evolutionary Algorithms

Decoding function

Genetic operators

Genotype space(Genetic representation)

G(t)

references selected prior work related to embedded software optimization
References: selected prior work related to embedded software optimization
  • 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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