Daler N. Rakhmatov, Associate Professor
Electrical and Computer Engineering
University of Victoria

Green Computing Innovations for Biomedical Imaging Applications

Our research tackles technical challenges associated with enhancing energy efficiency and reusability of battery-powered embedded systems targeting computation-intensive biomedical imaging applications. We take an application-centric approach, providing for high energy efficiency through sufficient application-driven system specialization, while supporting needed reusability through sufficient application-aware system flexibility. We pursue the following four lines of inquiry:
  • Low-complexity image formation techniques for biomedical ultrasound applications, aiming to reduce the energy cost of multidimensional data acquisition, processing, and analysis;

  • Configurable hardware/software architectures for supporting computation-intensive imaging tasks, to enable high-performance, low-power, and flexible application execution;

  • Predictive analytical models of nonlinear dynamics of the system energy supply and demand, to facilitate battery-aware system-level optimizations (e.g., hardware/software partitioning, data precision, operation scheduling);

  • Model-driven configuration algorithms that automatically tune hardware/software component organization and programming, to maximize system service quality subject to battery-imposed energy constraints during targeted application execution.

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