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Power estimation

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Title: No Slide Title Author: Mehdi Amirijoo Last modified by: Aleksandra Tesanovic Created Date: 11/8/2001 5:28:46 AM Document presentation format – PowerPoint PPT presentation

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Title: Power estimation


1
Power estimation
  • General power dissipation in CMOS
  • High-level power estimation metrics
  • Power estimation of the HW part
  • Power estimation of the SW part
  • Simulations and results
  • Source
  • W. Fornaciari, P. Gubian, D. Sciuto, C.
    Silvano
  • Power Estimation of Embedded Systems.
  • IEEE Transactions on VLSI systems, V6, N2,
    1998

2
General power ...
  • Estimating from system-level point of view.
  • Average power is related to the switching
    activity of the circuit nodes.
  • Power dissipation in CMOS devices is composed of
    a static and a dynamic part. Dynamic part is the
    most dominant.
  • CEFF is the effective switched capacitance.

3
General power ...
  • ?i is the switching activity factor at node i. We
    assume spatial and temporal independence between
    nodes.
  • Also define the toggle rate as

4
High-level power estimation
  • The power dissipation in timing-constrained
    systems depends on the mode of computation
  • Fixed throughput
  • Maximum throughput
  • Burst throughput
  • Metric for Fixed throughput
  • Metric for Maximum throughput

5
High-level power estimation
  • Metric for Burst throughput
  • Systems with power shutdown techniques, ETR else
    MBurst
  • For an area-constrained system the following
    metric is efficient

6
Power Estimation of HW part
  • Analytical model based on VHDL description at
    behavioral/RT level and the probabilistic
    estimation of the internal switching activity.
  • Hierarchical estimation approach.
  • User supplied input probabilities rather than
    input patterns.
  • Assumptions
  • The supply and ground voltage are fixed.
  • Synchronous sequential circuits.
  • Data transfer at register-register level.
  • ZDM

7
Power Estimation of HW part
  • Inputs to the estimation
  • The ASIC spec.
  • The allocation library, components implementing
    the macro-modules and the basic modules.
  • The technological parameters.
  • The switching activity of the I/Os
  • The total average power dissipation is given by
  • Average power dissipated by the I/O nets
  • Core internal nets

8
Power Estimation of HW part
  • Data-path PDP , memory PMEM , control logic
    PCNTR , core processor PPROC
  • For estimating the PIO factor requires knowledge
    about switching activity (given by the spec) and
    the pad characteristics (capacitance etc).
  • PDP is divided into the following

9
Power Estimation of HW part
  • PMEM is proportional to
  • and
  • We assume to have Pi,m in the target library

10
Power Estimation of HW part
  • P can be divided into
  • Model the control unit as a probabilistic FSM -
    Markov chain.
  • The input signal probabilities (input switching
    activity factors) are obtained from the
    system-level specification. Also assume ZDM.
  • The average power dissipated by the kth input,
    depends on the switching activity factor ?k and
    the input load capacitance Ck

11
Power Estimation of HW part
  • Px(Cx) is the average power consumption per MHz.
  • Let pij P(next sj present si),
    conditional state transition probability.
  • Let Pi be the steady state probability of the
    state si (the probability to be in a certain
    state in an arbitrarily long sequence. Given the
    Markov chain we can solve this problem by solving
    the Chapman-Kolmogorov equations).
  • Let Pij pijPi be the total state transition
    probability.

12
Power Estimation of HW part
  • TP, transition probability between two disjoint
    subsets
  • S s1, s2, . , sn
  • Si and Sj are disjoint subsets of S
  • Power dissipation of register (in general) can be
    divided into a switching and non-switching power.

13
Power Estimation of HW part
  • Switching power Pi relates to the toggle rate
    TRbi of the output of the register, while the
    PNSi relates to the power consumption during the
    clock edges.
  • Pi (or TRbi)depends on the state switching
    activity and the state encoding.
  • bi is the ith bit of the state code (state bit).

14
Power Estimation of HW part
  • Estimation of PCOMB
  • Assume a gate X.
  • Ci is the capacitance driven by the ith gate X.
  • Pi(Ci) is the average power consumption per MHZ
    of the ith gate X.
  • TRi is toggle rate of the gate X (based on the
    probabilistic model of switching activity of X).

15
Power Estimation of HW part
  • Moore-type FSM,
  • Power dissipation of POUT is composed of a part
    related to the combinatorial net and a part
    related to the primary outputs driving the output
    capacitance.
  • The total state transition probabilities Pij
    between two states si and sj are equal to the
    total transition probabilities between the
    corresponding outputs oi and oi

16
Power Estimation of SW part
  • Bottom-up approach (TOSCA).
  • In TOSCA the specification is compiled in the
    VIS, by considering the average power consumption
    of each VIS instruction during the execution of a
    given program. Choosing VIS-level makes the
    analysis processor independent.
  • Estimate the power consumption of each block.
  • Estimate the total power consumption by weighing
    the power consumption of each block according to
    execution frequencies.

17
Power Estimation of SW part
  • In general
  • The average current or energy (VDD is fixed) of
    each instruction can be derived by
  • Measurements or detailed information from the
    provider
  • However we have overheads in forms of pipeline
    stalls, cache misses etc.
  • The overheads have been measure to be less than
    5 of the base energy per instruction.
  • Add the overheads to the base energy cost.

18
Simulations and results
  • Background
  • 35 FSMs from the MCNC-91 benchmark suite.
  • HCMOS6 tech, 0.35 um, 3.3 V, 100 MHz
  • FSMs synthesized by Synopsys Design Compiler
  • Comparing to Sysnopsys Design Power (based on the
    synthesized gate-level netlist).
  • Average percentage error of 9.52 (0.01-25.8)

19
Simulations and results
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