threshold-carryselect-adder

4-bit carry-select adder as threshold circuit. Faster than ripple-carry by pre-computing results for both possible carry values.

Circuit

A[3:0] ──┐
B[3:0] ──┼──► CSel Adder ──┬──► S[3:0]
Cin    ──┘                 └──► Cout

How It Works

Block 0 (bits 0-1): Ripple-carry with actual Cin
  └──► produces C1 (carry into bit 2)

Block 1 (bits 2-3): Pre-compute BOTH possibilities
  Path A: assume Cin=0 → S2_0, S3_0, Cout_0
  Path B: assume Cin=1 → S2_1, S3_1, Cout_1

Final: MUX selects Path A or B based on C1

Timing Advantage

Ripple-Carry:  [FA0]──►[FA1]──►[FA2]──►[FA3]  (4 stages)

Carry-Select:  [FA0]──►[FA1]──┐
               [HA2]──►[FA3]  ├──►[MUX]  (3 stages)
               [FA2]──►[FA3]──┘

Block 1 computes in parallel with Block 0.

Architecture

Component	Count	Neurons
Block 0 (2 FAs)	2	14
Block 1 cin=0 (HA+FA)	2	11
Block 1 cin=1 (2 FAs)	2	14
Output MUXes	3	9

Total: 48 neurons, 149 parameters, 4 layers

Trade-offs

• More neurons than ripple-carry (48 vs ~28)
• Faster critical path (3 stages vs 4)
• Scales well: 8-bit uses 4x2-bit blocks

Usage

from safetensors.torch import load_file

w = load_file('model.safetensors')

# All 512 test cases verified (16 × 16 × 2)

Files

threshold-carryselect-adder/
├── model.safetensors
├── create_safetensors.py
├── config.json
└── README.md

License

MIT