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M. Ibrahim Halas, M. Rupp:
"Embedded Systems Code Optimization and Power Consumption";
in: "Embedded and Networking Systems: Design, Software, and Implementation", issued by: Kris Iniewski; John Wiley & Sons, 2013, 85 - 104.

The increasing demand for portable computing has elevated power consumption to be one of the most critical embedded systems design parameters. In this chapter, we investigate several software optimization techniques for embedded-processor systems. As a specific example, we consider the powerful Texas Instruments C6416T DSP. We assess the effect of the compiler performance optimizations on the energy and power consumption. Moreover, we explore the impact of employing two special architectural features of this DSP; namely Software Pipelined Loop (SPLOOP) and the Single Instruction Multiple Data (SIMD) capability via the utilization of compiler intrinsic C-functions, on the energy and power consumption.
The currently-available compiler optimization techniques are handicapped for power optimization due to their partial perspective of the algorithms and due to their limited modifications to the data structures. On the contrary, other software optimization techniques, like source code transformations, can exploit the full knowledge of the algorithm characteristics, with the capability of modifying both data structures and algorithm coding. Furthermore, inter-procedural optimizations are envisioned. Hence, we investigate several loop, data and procedural source code transformations from the power and energy perspectives.

The increasing demand for portable computing has elevated power consumption to be one of the most critical embedded systems design parameters. In this chapter, we investigate several software optimization techniques for embedded-processor systems. As a specific example, we consider the powerful Texas Instruments C6416T DSP. We assess the effect of the compiler performance optimizations on the energy and power consumption. Moreover, we explore the impact of employing two special architectural features of this DSP; namely Software Pipelined Loop (SPLOOP) and the Single Instruction Multiple Data (SIMD) capability via the utilization of compiler intrinsic C-functions, on the energy and power consumption.
The currently-available compiler optimization techniques are handicapped for power optimization due to their partial perspective of the algorithms and due to their limited modifications to the data structures. On the contrary, other software optimization techniques, like source code transformations, can exploit the full knowledge of the algorithm characteristics, with the capability of modifying both data structures and algorithm coding. Furthermore, inter-procedural optimizations are envisioned. Hence, we investigate several loop, data and procedural source code transformations from the power and energy perspectives.

embedded systems

http://publik.tuwien.ac.at/files/PubDat_217753.pdf

Project Head Markus Rupp:
Embedded Computer Vision