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