One of the biggest challenges in FPGA programming is the process of quantizing mathematical operations to fixed-point for more efficient implementation.

This session teaches the fundamentals of the fixed-point number system and fixed-point arithmetic, along with considerations for targeting popular FPGA devices. These concepts are then reinforced through practical demonstrations, capped by walking through the process of quantizing a signal processing design.

Topics include:

Fixed-point theory
Fixed-point number system
Mathematical range
Quantization error in the time and frequency domains
Common functions
Arithmetic: square root, reciprocal, log2
Trigonometry: cosine, sine, atan2
Signal processing: FIR, FFT
FPGA considerations
Targeting Xilinx and Intel devices
Maintaining precision
Using native floating point for full-precision calculations
Example: communications packet detection
Matched filter
Peak detection
FPGA optimizations