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Instantaneous Current Modelling at the Instruction Level

Instantaneous Current Modelling at the Instruction Level. Dr Chris Bleakley. Overview. Estimation of processor current consumption is important for the design of low power systems.

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Instantaneous Current Modelling at the Instruction Level

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  1. Instantaneous Current Modelling at the Instruction Level Dr Chris Bleakley

  2. Overview • Estimation of processor current consumption is important for the design of low power systems. • Instruction-Level Power Analysis (ILPA) models predict a processor's average current consumption based on an analysis of the trace of executed assembly language instructions. • Conventional ILPA models estimate the average current over hundreds of instruction cycles. • This paper proposes a novel method for estimating the dynamic (cycle-by-cycle) current consumption of a processor.

  3. Motivation • Estimation of processor current based on an analysis of the software is: • Much faster and cheaper than performing physical measurements • Provides the programmer with more information on the causes of current consumption • Estimation of dynamic current has applications in: • current smoothing for prevention of cryptographic attacks and for extension of battery life • identifying 'quiet periods' for RF reception • power supply system design

  4. Motivation • In processors with high degrees of parallelism, current varies considerably from instruction to instruction and between modes.

  5. Current Solutions • Spreadsheet • included in the TI SDK

  6. Current Solutions • Oscilloscope • Jumpers provided on TI Evaluations Boards for measuring supply current • LabVIEW USB measurement systems • recent product from TI and National Instruments • TI C55X Power Optimization DSP Starter Kit

  7. Current Solutions • Spreadsheet • Designers must guess the parameters • Even if the parameters are correct, the spreadsheet still gives the wrong answer • The spreadsheet gives a worst case average, no temporal information • Measurements • If done right, it is accurate • TI/NI kit only accurate to 40 kHz • Difficult and time consuming to set-up and configure hardware • Difficult to capture entire application • Gives no insight on what is causing dissipation • Hard to use

  8. Conventional ILPA Model • Proposed by Tiwari Ep = energy consumption of program Bi = base energy consumption of instruction i No = number of occurrences of instruction i Oi,j = inter-instruction effect for the instruction pair i,j Ni,j = number of occurrences of the pair i,j Ek = other effects

  9. Conventional ILPA Model • Models the TOTAL energy consumed by execution of an instruction • Does not model WHEN the energy is consumed • Due to capacitance and inductance in the power supply system, the energy is not consumed instantaneously • This was noted by Gebotys who modelled the "instantaneous current" resulting from execution of a single instruction by fitting a gamma function

  10. Dynamic Current

  11. xd[n] ye[n] LTI system hi [n] Proposed Dynamic Model • We model the dynamic current consumption as the output of a linear system excited by an input signal consisting of the total current consumption for each successive instruction (i.e. Tiwari model evaluated one instruction at a time)

  12. Proposed Dynamic Model ye[n] = estimated current at clock cycle n hi[k] = impulse response of the system at clock cycle k xd[n] = total current due to instruction executed at clock cycle n N = length of impulse response in clock cycles

  13. Proposed Dynamic Model • Assumptions: • System is Linear Time Invariant (LTI): • some non-linearity in voltage regulator • Dynamic current profile is the same for all instructions • not true, different instructions consume different proportions of energy in different stages of the pipeline • but impulse response is much longer than pipeline so impact is small • Tiwari model is accurate • extended model to improve accuracy for processor under investigation, achieved accuracy >= 98% • 1.5% error due to data dependency

  14. System Identification • Goals: • to identify the system as a 3rd party, i.e. no knowledge of the electrical properties of the power supply system • to achieve high SNR with minimal number of measurements • to rely on as few characterised instructions as possible • Method: • Cross-correlation method utilising maximal length sequences as stimulus

  15. System Identification x[n] = system input y[n] = system output h[n] = impulse response of the system Rxy[l] = cross-correlation of the input and output Rxx[l] = auto-correlation of the input

  16. System Identification Rmm[l] = circular auto-correlation of m-sequence • M-sequence is pseudo-random, generated by Linear Feedback Shift Register (LFSR) • M-sequence is two valued (-1,1), e.g. [1,-1,1,…] • M-sequence has period 2m-1, where m is the number of registers in the LFSR.

  17. Method • Texas Instruments TMS320C5510 DSP • Up to 120% variation in current consumption between different instructions

  18. Method • Developed conventional ILPA model. • Generated stimulus program from m-sequence mapping -1 to NOP and +1 to dual MAC instructions. • Executed stimulus program within long loop. • Captured current trace from oscilloscope (averaged). • Applied cross-correlation method to obtain impulse response of system. • Extracted kernels from 5 benchmark programs. • Captured current trace for benchmarks. • Estimated current trace using ILPA and dynamic model. • Compared measured and estimated current traces.

  19. Results (a) cfft (b) iir4 (c) log10 (d) jpeg_qize (e) dct_idct

  20. Results

  21. Power Composer • Runs cycle accurate simulation of program • Parses each instruction • Estimates current consumption per instruction • Uses model derived from measurements • Takes into account instruction scope • Extracts model parameters from pre-computed database • Estimate current consumption per cycle • Uses model derived from measurements • Generates current plot and report

  22. Power Composer

  23. Grammar and Vocabulary Rules Input 1: source.asm Code Composer Studio (TI) Power Composer Core (Plug-in) Parser Xml API Xml StaticModel Report 1: Current per instruction Estimator kernel SDK Servers Dynamic Model File Report 2: Current per cycle Cycle Accurate Simulator (TI) Power Composer

  24. Conclusions • Proposed a novel model for estimation of the dynamic current consumption of a processor based on an analysis of the instruction trace. • Described an experimental method for identification of the dynamic model. • The model and method were applied to a commercial DSP processor. When compared with measurement, the estimates were shown have a squared correlation coefficient of 87% or greater across a range of benchmarks.

  25. Acknowledgements • This project was supported by Enterprise Ireland. • Thank you for your attention. • Questions…

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