Both Phase 2 findings (docs/FPGA-NeuralNetwork-Engine.md) shared one
root cause: GROUPS = N_INPUTS / PARALLEL is integer division. When
N_INPUTS is not an exact multiple of PARALLEL, the remainder inputs
were silently dropped from the accumulation (wrong result, no
error); when PARALLEL > N_INPUTS, GROUPS = 0 and the controller's
terminal condition was never met, hanging the neuron forever.
Added a single elaboration-time guard to rtl/neuron_parallel.v: a
`generate` block instantiates a deliberately undefined module when
N_INPUTS % PARALLEL != 0, forcing a hard failure in both simulation
and synthesis instead of a silent wrong answer or a deadlock. Valid
configurations are unaffected (the branch is never elaborated). The
validated datapath (mac8/mac_unit/accumulation/ReLU/saturation) is
untouched -- this is authorized as a scoped exception to the
"core is fixed, do not touch" project policy, for this guard only.
- sim/neuron_parallel_guard_negative_nonmultiple_tb.v and
sim/neuron_parallel_guard_negative_degenerate_tb.v: negative tests
that must fail to elaborate; verified both fail with the expected
"Unknown module type" error.
- sim/parameter_sweep_tb.v: rewritten to valid-configs-only (the
three configs that used to demonstrate truncation/hang no longer
compile, by design); added PARALLEL=2 and PARALLEL=4 configs,
the two best-performing values from
docs/FPGA-Neural-Datapatch-Benchmark.md.
- Full regression re-run after the RTL change: all existing
testbenches still pass unchanged.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WQV3vS9TXaGDJ5cRfnfidt
