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# Optimization: Cutoff (close-neighbors only)
- **Author**: Linus
- **Predecessor**: variant_baseline.cpp
- **File(s)**: variants/variant_cutoff_callsite.cpp (main version),
variants/variant_cutoff.cpp (first attempt, the cutoff check inside the function)
- **Status**: probably positive (approx. 1.4-1.8 times faster on my laptop)
## What this changes
Skip the full force computation for pedestrian pairs whose squared distance
exceeds `CUTOFF_SQ` (CUTOFF = 5.0 m in `headers/constants.hpp`). At that
distance the truncated `exp(-r/sigma)` factor is `~6e-8` per pair
Two placements of the check were tried:
- **First attempt** (`variant_cutoff.cpp`): check at the top of
`pedestrian_repulsion_dt`. Function call still happens for every pair, only
the actuall calculation is skipped for far pairs.
- **Main version** (`variant_cutoff_callsite.cpp`): check is before te
call in `run_simulation`. Far pairs skip the function call entirely,
and the redundant in-function check was removed.
We picked CUTOFF=12 (not 5) so that `make verify` passes the full 4000-step
diff. At 12 m, the truncated per-pair force is around 1e-20, below the
double-precision rounding threshold for the accumulator, so the FP result
stays bit-identical to baseline. Trade-off: speedup drops from ~3-4x at
CUTOFF=5 to 1.4-1.8x at CUTOFF=12, we kept the strict version for
correctness.
For the CUTOFF=5:
Default `make verify` fails because cutoff causes tiny FP drift, and once a pedestrian wraps around the corridor end one step earlier than the baseline, its position diff jumps by ~47 m and the comparison breaks. Workaround: verify against a short 200-step reference where no teleports have happened yet.
```bash
./main_baseline 60 200 reference/baseline_n60_i200.csv # one-time setup
./main_cutoff_callsite 60 200 verify_cutoff_callsite_short.csv
python3 scripts/verify.py reference/baseline_n60_i200.csv verify_cutoff_callsite_short.csv 1e-3
```
## Code (relevant snippet)
In `run_simulation`, the inner pair loop:
```cpp
for (int j = 0; j < n_p; j++) {
if (i == j)
continue;
// Cutoff at the call site
Vector2d r_ab_pre = p.curr_pos - pedestrians[j].curr_pos;
if (r_ab_pre.x * r_ab_pre.x + r_ab_pre.y * r_ab_pre.y > CUTOFF_SQ)
continue;
f_alpha_dt += pedestrian_repulsion_dt(p, pedestrians[j]);
}
```
`pedestrian_repulsion_dt` no longer has its own cutoff.
Constants added to `headers/constants.hpp`:
```cpp
const double CUTOFF = 5.0;
const double CUTOFF_SQ = CUTOFF * CUTOFF;
```
## Benchmark
Conditions: min of <N> runs, N_ITER=1000, -O3 -march=native -flto.
A preliminary run on my laptop (Intel ULTRA 9 185H @ 2.2 GHz, WSL
Ubuntu) showed both variants 3-4x faster than the baseline across N=50 to
N=1000, with the callsite version about 4-5% faster than the in-function
version. The speedup was roughly constant across N.
### x86
**Machine**:
```
<paste machine info here>
```
**Frequency**: <e.g., 2 GHz>
Main version (`variant_cutoff_callsite.cpp`):
| N | W(n) [Flops] | T(n) [Cycles] | Performance [Flops/Cycle] | Diff vs Baseline |
| ---- | ------------ | ------------- | ------------------------- | ---------------- |
| 50 | | | | |
| 100 | | | | |
| 200 | | | | |
| 500 | | | | |
| 1000 | | | | |
First attempt (`variant_cutoff.cpp`) for comparison:
| N | W(n) [Flops] | T(n) [Cycles] | Performance [Flops/Cycle] | Diff vs Baseline | Diff vs Main |
| ---- | ------------ | ------------- | ------------------------- | ---------------- | ------------ |
| 50 | | | | | |
| 100 | | | | | |
| 200 | | | | | |
| 500 | | | | | |
| 1000 | | | | | |
### ARM (Apple)
**Machine**:
```
<paste machine info here>
```
**Frequency**: <e.g., 3.2 GHz>
Main version (`variant_cutoff_callsite.cpp`):
| N | W(n) [Flops] | T(n) [Cycles] | Performance [Flops/Cycle] | Diff vs Baseline |
| ---- | ------------ | ------------- | ------------------------- | ---------------- |
| 50 | | | | |
| 100 | | | | |
| 200 | | | | |
| 500 | | | | |
| 1000 | | | | |
First attempt (`variant_cutoff.cpp`):
| N | W(n) [Flops] | T(n) [Cycles] | Performance [Flops/Cycle] | Diff vs Baseline | Diff vs Main |
| ---- | ------------ | ------------- | ------------------------- | ---------------- | ------------ |
| 50 | | | | | |
| 100 | | | | | |
| 200 | | | | | |
| 500 | | | | | |
| 1000 | | | | | |
## Analysis
<Why it worked or did not. What surprised you. What bottleneck this hits
or moves. Mention generated assembly or a profile if relevant.>
## Takeaway
<One short paragraph that could be lifted straight into the report.>