Hardware Metrics Scaling Calculator

Calculate key hardware performance metrics and estimate scaled performance across different technology nodes. Enter baseline parameters for your design and explore how area efficiency and energy efficiency change with technology scaling.

Key Metrics

Performance Metrics
  • Area Efficiency: $\text{AE} = \frac{\text{Throughput (Gbps)}}{\text{Area (mm}^2\text{)}}$ (Gbps/mm²)
  • Energy Efficiency: $\text{EE} = \frac{\text{Power (mW)}}{\text{Throughput (Gbps)}}$ (pJ/bit)
  • Dynamic Power: $P \approx C \times V_{DD}^2 \times f$ (dynamic power)
  • Throughput: $\frac{\text{Code Length (bits)}}{\text{Time for a new output to appear (ns)}}$ (Gbps)
  • Information Throughput: $\frac{\text{Message Length (bits)}}{\text{Time for a new output to appear (ns)}}$ (Gbps)
CMOS Scaling Rules

Typical scaling from node size $n_1$ to $n_2$ with voltage $V_1$ to $V_2$:

  • Area Factor: $AS = \left(\frac{n_2}{n_1}\right)^2$
  • Energy Factor: $ES=\left (\frac{V_2}{ V_1} \right)^2 \times \left( \frac{n_2}{n_1}\right)^2$
  • Scaled Area Efficiency: $\text{AE}_{scaled} = \frac{\text{Throughput (Gbps)}}{\text{Area (mm}^2\text{)} \times AS}$ (Gbps/mm²)
  • Scaled Energy Efficiency: $\text{EE}_{scaled} = ES \times \frac{\text{Power (mW)}}{\text{Throughput (Gbps)}}$ (pJ/bit)

Note: Actual scaling depends on design, architecture, and process variations. Scaling parameters obtained from: C. -H. Lin, C. -Y. Chen, A. -Y. Wu and T. -H. Tsai, "Low-Power Memory-Reduced Traceback MAP Decoding for Double-Binary Convolutional Turbo Decoder," in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 56, no. 5, pp. 1005-1016, May 2009, doi: 10.1109/TCSI.2009.2017118.


Baseline Calculator

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Baseline Results

    Technology Scaling Estimator

    Select target technology nodes to estimate scaled performance:

    Technology nodes to compare
    Corresponding VDD values
    Scaled Estimates

    Notes on Scaling

    Important Considerations
    • Simplified Model: This calculator uses simplified CMOS scaling rules. Real designs face more complex tradeoffs.
    • Architecture Impact: Scaling may enable architectural changes (more parallelism, pipelining) not captured here.
    • Leakage Power: Static power becomes dominant at smaller nodes and is not fully modeled.
    • Design Complexity: Smaller nodes often require more sophisticated design techniques.
    Typical Technology Nodes
    • 180nm: ~1.8V, legacy designs
    • 90nm: ~1.2V, mature process
    • 65nm: ~1.1V
    • 45nm: ~1.0V
    • 28nm: ~0.9V, widely used
    • 16nm/14nm: ~0.8V, FinFET
    • 7nm: ~0.75V, advanced FinFET
    • 5nm: ~0.7V, leading edge
    • 3nm: ~0.65V, cutting edge



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