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Author SHA1 Message Date
micheleandClaude Sonnet 5 07a48e401f fix: close 7 zero-value/mid-run guard gaps found in re-certification campaign 
Fixes all 7 bugs found in the FPGA-Neural re-certification campaign
(docs/validation/bugs.md, CERTIFICATION.md), per campaign policy that
fixes land as a commit separate from the analysis work (commits
313a199..77e74db):

- BUG-005 (CRITICAL): layer_sequencer.v -- RUN_NETWORK(num_layers=0)
  ran through 256 fabricated layers reading arbitrary PSRAM data as
  descriptors. Now an immediate no-op.
- BUG-007 (CRITICAL): spi_engine.v -- SET_NET_TYPE received mid-run
  remapped the arbiter mux and hung the in-progress engine. Now
  rejected while graph_busy/seq_busy, verified not to partially apply.
- BUG-002 (MEDIA): neuron_parallel.v -- N_INPUTS=0 bypassed the
  elaboration-time guard, leaving x_bus/w_bus undriven. Guard extended
  to reject N_INPUTS==0.
- BUG-003 (MEDIA): neuron_parallel.v -- n_inputs_real=0 at runtime had
  inconsistent behavior across repeated runs. Now an explicit early-out
  via the existing "finishing" completion path.
- BUG-004 (BASSA): neuron_memory.v -- n_neurons_real=0 silently ignored
  the limit. Fixed at all three entry points into the vulnerable
  termination checks (STATE_READ_X, STATE_READ_W, and the X->W
  dispatch).
- BUG-006 (BASSA): graph_engine.v -- num_neurons_graph=0 relied on an
  incidental guard rather than a real one. Now an explicit no-op.
- BUG-001 (INFO): removed sim/top.v, confirmed dead code from the
  pre-INT8 Q8.8 era.

Every bug-reproduction testbench is rewritten from observe-only to
hard-assert the fixed behavior (sim/*_bug00[2-7]*_tb.v), verified
individually and via a full regression (44 testbenches, 43 PASS, 0
FAIL/ERROR, 1 benchmark by design). Re-verified on the real toolchain
(Yosys synth_ecp5 + nextpnr-ecp5): 0 constraint errors, Fmax 68.65 MHz
(was 67.91 MHz, within known placement noise), critical path
structurally unchanged (neuron_parallel/mac8 accumulator carry chain).

Updates docs/validation/bugs.md and CERTIFICATION.md to reflect the
resolved state, and docs/FPGA-NeuralNetwork-Engine.md + the LaTeX
datasheet (IT/EN) with inline notes on each fixed edge case, closing
the datasheet/RTL gap flagged in C.13 of the original certification.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_013xXuuRUWZScuo1DeYJxs3v
 2026-09-04 20:29:05 +02:00
micheleandClaude Sonnet 5 7e2711fa27 feat: widen ADDR_WIDTH to 23 bits for full 8MB PSRAM addressing 
Bumps ADDR_WIDTH's default from 22 to 23 bits across every RTL
module (neuron_memory, layer_sequencer, spi_engine, spi_neuron_top,
mem_arbiter, int8_memory_access, memory_interface, psram_controller,
memory_model) and every testbench that mirrors it, so the system's
byte-address space reaches the full 8 MiB the recommended PSRAM part
(ISSI IS66WVE4M16EBLL-70BLI, docs/FPGA-Neural-Hardware-Design.md §3)
actually provides -- previously only 4 MiB (half the chip) was
reachable, since int8_memory_access.v's byte->word address shift
(addr >> 1) turned the old 22-bit byte address into only 21 real word
bits, one short of the chip's real 22-bit word address (A0-A21). At
23 bits, that same shift lands exactly on all 22 chip address lines,
so the whole part is usable now instead of deferred to a future
widening.

Also fixes a stray 22'd11-sized literal in layer_sequencer.v's
descriptor-table address increment (numerically already safe via
Verilog's zero-extension, but now correctly unsized so it always
matches ADDR_WIDTH instead of silently assuming 22).

Updated docs/FPGA-NeuralNetwork-Engine.md's SPI protocol address-field
note (23 bits, top 1 reserved bit instead of 2) and
docs/FPGA-Neural-Hardware-Design.md's PSRAM section (the "chip has
one spare address line" framing is gone now that all 22 are wired
and used).

Full regression (all 11 ADDR_WIDTH-touching testbenches, plus a
Yosys elaboration check of spi_neuron_top with the new default and
no override) passes clean.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WQV3vS9TXaGDJ5cRfnfidt
 2026-09-02 21:00:46 +02:00
micheleandClaude Sonnet 5 a918c3f1e9 feat: configurable activation functions + runtime-configurable network topology 
Two related Phase 5 additions, both threaded the same way (a new
runtime field defaulting to the pre-existing behavior, settable
per-layer via the descriptor table or per-run via SET_BASE):

Configurable activation functions:
- neuron_parallel.v gains a 2-bit `activation` port (ACT_NONE =
  linear + two-sided INT8 saturate, ACT_RELU = the original
  hardwired behavior, kept as the default so every pre-existing
  caller/testbench is unaffected), threaded through neuron_memory.v.
- spi_engine.v: SET_BASE sel=6 (single-layer path); the descriptor
  table gains a 7th byte (multi-layer path).
- Verified in neuron_parallel_tb.v (negative pass-through + negative
  saturation to -128) and end-to-end in
  spi_neuron_top_runnetwork_tb.v (a real negative accumulator that
  ACT_RELU would clamp to 0 comes through unclamped under ACT_NONE,
  over real SPI/RAM).

Runtime network width (one bitstream, any topology up to its
build-time max, entirely host-configured over SPI):
- neuron_parallel.v gains n_inputs_real, bounding its MAC group loop
  (n_inputs_real/PARALLEL groups instead of the fixed build-time
  count). neuron_memory.v gains n_inputs_real/n_neurons_real,
  bounding its X/W RAM-read loop and its neuron loop. All default to
  the build-time max, so unconnected callers are unaffected.
  n_inputs_real must stay a multiple of PARALLEL (same constraint
  N_INPUTS itself is held to at elaboration time, now the caller's
  runtime responsibility).
- spi_engine.v: SET_BASE sel=7/8 (single-layer path); the descriptor
  table grows to 11 bytes/layer (+n_inputs_real +n_neurons_real,
  multi-layer path) -- layer_sequencer.v also now copies only
  n_neurons_real bytes into the ping-pong buffer, not the full
  build width.
- This is real early termination, not bookkeeping: no RAM
  zero-padding needed for the unused tail, and it measurably
  completes faster. neuron_parallel_tb.v TEST 7: 3 cycles vs 6 for a
  reduced-vs-full run, with garbage loaded into the skipped lanes to
  prove they're never read. neuron_memory_tb.v TEST 5: through the
  real PSRAM stack, 209 cycles vs 788. layer_sequencer_tb.v proves a
  reduced n_neurons_real shortens the ping-pong copy-out itself
  (bytes beyond the real count stay untouched, not just differing).

docs/FPGA-NeuralNetwork-Engine.md: §8.1 opcode/SET_BASE table, new
"Runtime network width" subsection, Phase 5 checklist, Current
Status table, and the "Core architectural principle" statement
updated to reflect that topology (not just trained parameters) is
now host-configured at runtime up to a build-time ceiling.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WQV3vS9TXaGDJ5cRfnfidt
 2026-09-02 20:18:24 +02:00
michele 233d6ff7fb feat: complete Phase 5 multi-layer network (RUN_NETWORK) + fix STATUS race 
Wires the already-present layer_sequencer.v into the SPI stack:

- spi_engine.v: RUN_NETWORK opcode (0x23) + SET_BASE selectors for
  table_base/buf_a_base/buf_b_base; STATUS.busy/done extended to
  track the sequencer (seq_busy/seq_done) alongside neuron_memory
  directly, so done latches on the last layer only.
- spi_neuron_top.v: instantiates layer_sequencer, muxes
  neuron_memory's control inputs between it (while seq_busy) and
  spi_engine's direct-drive path (legacy single-layer mode), wires
  the sequencer's own RAM master to mem_arbiter's Port C.

Found and fixed a real race while writing the end-to-end test: STATUS's
sticky/clear-on-read done bit read its value live/combinationally
during transmission and cleared unconditionally on any STATUS read.
A done_event landing mid-transmission of a STATUS response byte could
be silently dropped -- the host would receive a stale byte while the
sticky bit was cleared regardless, hanging any host polling STATUS in
a loop. Present since Phase 4, not RUN_NETWORK-specific; only
surfaced under this test's continuous polling. Fixed by latching a
status_snapshot at opcode-accept time and gating the clear on what
was actually transmitted.

Tests: spi_engine_tb.v gains RUN_NETWORK/SET_BASE opcode tests (K/L);
new layer_sequencer_tb.v unit-tests the sequencer FSM directly
(descriptor table, ping-pong buffer addressing, byte-exact copy-out);
new spi_neuron_top_runnetwork_tb.v drives a real 2-layer network over
simulated SPI end to end (real neuron_memory + PSRAM, hand-computed
expected output) and confirms the legacy single-layer path still
works afterward. All existing testbenches still pass.
 2026-09-02 19:47:36 +02:00