Energy Profiling of DSP Applications, A Case Study of an Intelligent ECG Monitor
Proper balance of power and performance for optimum system organization requires precise profiling of the power consumption of different hardware subsystems as well as software functions. Moreover, power consumption of mobile systems is even more important, since the battery is a large portion of the overall size and weight of the system. Average power consumption is only a crude estimate of power requirements and battery life; a much better estimate can be made using dynamic power consumption. Dynamic power consumption is a function of the execution profile of the given application running on specific hardware platform. In this paper we introduce a new environment for energy profiling of DSP applications. The environment consists of a JTAG emulator, a high-resolution HP 3583A multimeter and a workstation that controls devices and stores the traces. We use Texas Instruments’ Real Time Data Exchange mechanism (RTDXÔ) to generate an execution profile and custom procedures for energy profile data acquisition using GPIB interface. We developed custom procedures to correlate and analyze both energy and execution profiles. The environment allows us to improve the system power consumption through changes in software organization and to measure real battery life for the given hardware, software and battery configuration. As a case study, we present the analysis of a real-time portable ECG monitor implemented using a Texas Instruments TMS320C5410-100 processor board, and a Del Mar PWA ECG Amplifier.
Summary
This paper introduces a practical environment and methodology for dynamic energy profiling of DSP applications, demonstrated through a case study of an intelligent ECG monitor. Readers will learn how execution tracing (via JTAG/emulation) correlated with high-resolution power measurement reveals runtime energy behavior and guides low-power design decisions for real-time embedded DSP systems.
Key Takeaways
- Measure dynamic energy by correlating JTAG/emulator execution traces with high-resolution current/power measurements to reveal fine-grained power behavior.
- Identify software and hardware hotspots by mapping functions and code regions to their energy contributions for targeted optimization.
- Estimate battery life more accurately using dynamic execution profiles instead of crude average-power assumptions.
- Reduce system power by selecting or reordering algorithms and implementation strategies based on measured energy-per-operation tradeoffs.
- Apply the presented profiling environment and methodology to other mobile medical and real-time DSP systems to prioritize low-power changes.
Who Should Read This
Embedded systems engineers and firmware/software developers working on low-power real-time DSP devices (particularly medical wearables) who need practical methods to measure and reduce application energy consumption.
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