Fixed‑Point Implementation of a Simple Function
In this demo, we walk through how to implement a simple function using fixed‑point arithmetic. To keep the example focused, we consider a piecewise linear function:
y = max(a0*x + a1, a2*x + a3)
Why Fixed‑Point?
Fixed‑point arithmetic is widely used in digital hardware because it offers deterministic behavior, low latency, and efficient resource usage compared to floating point. Many embedded systems, DSP blocks, and accelerators operate under tight area, power, or timing constraints, making floating‑point units impractical. By choosing appropriate bit‑widths, we can achieve excellent numerical accuracy while keeping the implementation small, fast, and synthesizable.
What You Will Learn
By working through this demo, you will learn to:
- Implement and simulate a fixed‑point version of a nonlinear function in Python
- Measure the approximation error introduced by fixed‑point quantization and choose appropriate bit‑widths
- Generate test vectors from a Python golden model of the fixed‑point function
- Implement the same fixed‑point function in SystemVerilog and validate the RTL against the golden test vectors
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