Post-M10, user-requested final benchmark campaign: 6 realistic workloads (16-256 independent neurons in a shared-input dense-layer shape, a random-seeded 2-layer network with real cross-node PSRAM forwarding, and a 6-node 2-hop dependency diamond) x 4 concurrency levels (N_SLOTS=1/2/4/8) through the real, full neural_multiprocessor system (real V1 PSRAM chain, real slot_mem_arbiter). 24/24 runs PASS bit-exact against a software golden model (11,520 individual neuron/ node checks, zero mismatches). Three real bugs found and fixed during the campaign itself (ERR-0009): 1. neural_director.v (M5) had a real RTL bug at N_SLOTS=1 ($clog2(1)=0 makes a replication expression illegal) - never caught because M5-M10 only ever tested N_SLOTS=2/4/8. Fixed with a width-agnostic '0 literal; M5's own testbench re-verified unaffected. 2/3. Two testbench sizing bugs in tb_benchmark_suite.v itself (psram_model DEPTH too small for the Large workload's address range; N_NODES too small for the Stress workload's node-id range, causing a real deadlock via node-id wraparound colliding with an already-DISPATCHED node - a real, honest consequence of DEC-0008's own "no node-slot reclamation" design choice). Headline finding: real parallel scaling is essentially flat beyond N_SLOTS=2 - the single shared PSRAM port saturates at ~91% utilization regardless of slot count, so memory-bound workloads gain only 1.05-1.06x real speedup from N=1 to N=8. Once real POST-P&R Fmax degradation is also factored in, N_SLOTS=4 is measurably 21% SLOWER in real wall-clock time than N_SLOTS=1 for the largest workload tested. N_SLOTS=2 is recommended as the default (DEC-0014, superseding DEC-0012's resource-only "N_SLOTS=8 ceiling" framing for general use). Full 21-section report (every number classified THEORETICAL/ SIMULATED/POST-P&R MEASURED/DERIVED, per the user's own methodology requirements): hardware/v2/docs/benchmarks/ final-benchmark.md Logged: simulation/synthesis/timing/benchmark/decisions (DEC-0014)/ experiments (EXP-0014)/errors (ERR-0009)/development.log, ROADMAP.md updated. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_013xXuuRUWZScuo1DeYJxs3v
593 lines
28 KiB
Verilog
593 lines
28 KiB
Verilog
`timescale 1ns/1ps
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// ================================================================
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// FPGA-Neural V2 -- Final Benchmark Campaign (post-M10, real
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// end-to-end characterization, docs/v2-description.md §22/§30/§32)
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//
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// One testbench, compiled once per N_SLOTS configuration (N_SLOTS_CFG
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// parameter, overridden at Verilator invocation via -GN_SLOTS_CFG=N),
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// running SIX representative workloads back-to-back through the REAL
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// neural_multiprocessor.v (M8: dataflow_core + slot_mem_arbiter + the
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// real, unmodified V1 PSRAM chain), with:
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// - a software "golden" model replicating neural_processor.v's exact
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// integer math (sum(x*w) over all tiles, ReLU + INT8 saturate --
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// dataflow_core.v hardcodes bias=0/ACT_RELU for every job, so the
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// golden model only needs to replicate that one path)
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// - bit-exact verification of EVERY neuron's real result against
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// that golden model (peek_byte from the real psram_model backing
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// array -- an oracle independent of the RTL under test)
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// - real cycle-accounting instrumentation (testbench-only, no RTL
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// touched): per-slot busy/idle cycles, shared PSRAM port busy/idle
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// cycles, REAL tiles delivered per slot (operand_valid&&
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// operand_ready pulses -- one pulse = one whole P_IN-wide tile
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// consumed by neural_processor, NOT one byte), director/dependency
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// bookkeeping (jobs allocated/completed, ready-queue occupancy,
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// WAITING/READY/DISPATCHED node counts, producer-done wakeups)
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//
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// Workloads (node_id ranges are disjoint across all six so the WHOLE
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// campaign runs in ONE continuous simulation -- only ONE real PSRAM
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// power-up wait, no reset between phases, closer to real sustained
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// operation than resetting between every workload):
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// A) Small -- 16 independent neurons, 8 inputs each
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// B) Medium -- 64 independent neurons, 32 inputs each
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// C) Large -- 128 independent neurons, 128 inputs each
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// D) Stress -- 256 independent neurons, 128 inputs each
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// E) Multilayer -- 8 layer-1 neurons (RANDOM data, logged seed) feed
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// a shared 8-byte hidden vector; 2 layer-2 neurons
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// consume that vector (real cross-node data
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// forwarding through real PSRAM, real dependency
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// wake-up, "shared producer/multiple consumers")
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// F) DAG -- 6-node diamond+fan-in graph (A,B independent; C
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// dep on A; D dep on B; E dep on BOTH C and D
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// [2-hop transitive wake-up]; F dep on A,B,C [mixed
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// direct+1-hop, 3 producers])
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//
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// All workloads A-D use a REALISTIC dense-layer shape: one shared
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// input activation vector, N independent weight vectors (one per
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// neuron) -- exactly how a real fully-connected layer's neurons share
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// their layer's input. This is not an isolated synthetic microbench.
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//
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// Verified with Verilator (decisions.log DEC-0004).
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// ================================================================
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module tb #(
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parameter N_SLOTS_CFG = 2
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);
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localparam ADDR_WIDTH = 23;
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localparam DATA_WIDTH = 8;
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localparam P_IN = 8;
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localparam ACC_WIDTH = 32;
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// N_NODES must exceed the HIGHEST node_id used by ANY workload
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// (node_base + count - 1) -- workload D's own range alone
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// (node_base=400, 256 neurons) reaches id 655. An earlier draft
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// used N_NODES=512: D's ids silently wrapped (9-bit truncation)
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// past id 511, colliding with workload A's already-DISPATCHED
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// node 0 (dependency_manager never reclaims dispatched node slots,
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// DEC-0008) and deadlocking register_node's reg_ready wait
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// forever. A real consequence of DEC-0008's design choice, not an
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// RTL bug -- fixed here by sizing N_NODES generously above the
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// real id range used below (see decisions.log DEC-0008 and the
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// final benchmark report's Limitations section).
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localparam N_NODES = 1024;
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localparam MAX_DEPS = 8;
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localparam QUEUE_DEPTH = 8;
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localparam NODE_IDW = $clog2(N_NODES);
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localparam PSRAM_DATA_WIDTH = 16;
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localparam CLK_PERIOD = 12.5; // 80 MHz, matches psram_controller's CLK_FREQ_MHZ
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reg clk, rst;
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initial begin clk = 1'b0; forever #(CLK_PERIOD/2.0) clk = ~clk; end
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reg reg_valid;
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wire reg_ready;
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reg [NODE_IDW-1:0] reg_node_id;
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reg [$clog2(MAX_DEPS+1)-1:0] reg_required;
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reg [MAX_DEPS*NODE_IDW-1:0] reg_producer_ids;
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reg [ADDR_WIDTH-1:0] reg_x_base, reg_w_base, reg_result_addr;
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reg [15:0] reg_n_tiles;
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wire [ADDR_WIDTH-1:0] psram_a;
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wire [PSRAM_DATA_WIDTH-1:0] psram_dq;
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wire psram_ce_n, psram_oe_n, psram_we_n, psram_lb_n, psram_ub_n, psram_zz_n;
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neural_multiprocessor #(
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.DATA_WIDTH(DATA_WIDTH), .P_IN(P_IN), .ACC_WIDTH(ACC_WIDTH), .ADDR_WIDTH(ADDR_WIDTH),
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.N_SLOTS(N_SLOTS_CFG), .N_NODES(N_NODES), .MAX_DEPS(MAX_DEPS), .QUEUE_DEPTH(QUEUE_DEPTH),
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.PSRAM_DATA_WIDTH(PSRAM_DATA_WIDTH), .CLK_FREQ_MHZ(80)
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) u_nmp (
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.clk(clk), .rst(rst),
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.reg_valid(reg_valid), .reg_ready(reg_ready), .reg_node_id(reg_node_id),
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.reg_required(reg_required), .reg_producer_ids(reg_producer_ids),
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.reg_x_base(reg_x_base), .reg_w_base(reg_w_base), .reg_n_tiles(reg_n_tiles),
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.reg_result_addr(reg_result_addr),
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.psram_a(psram_a), .psram_dq(psram_dq),
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.psram_ce_n(psram_ce_n), .psram_oe_n(psram_oe_n), .psram_we_n(psram_we_n),
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.psram_lb_n(psram_lb_n), .psram_ub_n(psram_ub_n), .psram_zz_n(psram_zz_n)
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);
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// DEPTH (words) must cover the highest byte address used by any
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// workload's region (workload F's own base is the highest, ~0xB2000
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// bytes -> ~0x59000 words) -- an earlier draft used DEPTH=131072
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// (0x20000 words, covers only up to byte 0x40000) and silently
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// wrapped/out-of-bounds-accessed C-Large's result region
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// (0x048000 bytes -> word 0x24000, beyond that DEPTH) -- same bug
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// class as an M5 testbench bug already documented (errors.log/
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// simulation.log, sim_byte_mem's own too-small DEPTH). Fixed by
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// sizing DEPTH generously above the real address map used below.
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psram_model #(.ADDR_WIDTH(ADDR_WIDTH), .DATA_WIDTH(PSRAM_DATA_WIDTH), .DEPTH(524288)) u_psram (
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.clk(clk), .a(psram_a), .dq(psram_dq),
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.ce_n(psram_ce_n), .oe_n(psram_oe_n), .we_n(psram_we_n),
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.lb_n(psram_lb_n), .ub_n(psram_ub_n), .zz_n(psram_zz_n)
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);
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// ============================================================
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// Byte-level PSRAM backdoor access (test setup/verification only)
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// ============================================================
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task automatic poke_byte(input [ADDR_WIDTH-1:0] byte_addr, input signed [7:0] val);
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reg [ADDR_WIDTH-2:0] word_addr;
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begin
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word_addr = byte_addr[ADDR_WIDTH-1:1];
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if (byte_addr[0] == 1'b0) u_psram.mem[word_addr][7:0] = val;
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else u_psram.mem[word_addr][15:8] = val;
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end
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endtask
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function automatic signed [7:0] peek_byte(input [ADDR_WIDTH-1:0] byte_addr);
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reg [ADDR_WIDTH-2:0] word_addr;
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begin
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word_addr = byte_addr[ADDR_WIDTH-1:1];
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peek_byte = (byte_addr[0] == 1'b0) ? u_psram.mem[word_addr][7:0] : u_psram.mem[word_addr][15:8];
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end
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endfunction
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// Golden model: exactly replicates neural_processor.v's real path
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// through dataflow_core (bias=0, ACT_RELU always -- see
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// dataflow_core.v's own hardcoded job_bias/job_activation).
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function automatic signed [7:0] relu_sat(input integer acc);
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begin
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if (acc <= 0) relu_sat = 8'sd0;
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else if (acc > 127) relu_sat = 8'sd127;
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else relu_sat = acc[7:0];
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end
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endfunction
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// ============================================================
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// Node registration (generalized to MAX_DEPS=8 producers, passed
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// as a packed array; n_producers of them are meaningful, the rest
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// ignored since reg_required gates how many entries the RTL
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// actually reads).
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// ============================================================
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task automatic register_node(
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input [NODE_IDW-1:0] nid,
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input [$clog2(MAX_DEPS+1)-1:0] required,
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input [MAX_DEPS*NODE_IDW-1:0] producer_ids_packed,
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input [ADDR_WIDTH-1:0] xb, input [ADDR_WIDTH-1:0] wb,
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input [15:0] nt, input [ADDR_WIDTH-1:0] resaddr
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);
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begin
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@(posedge clk);
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reg_node_id = nid;
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reg_required = required;
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reg_producer_ids = producer_ids_packed;
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reg_x_base = xb; reg_w_base = wb; reg_n_tiles = nt; reg_result_addr = resaddr;
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reg_valid = 1'b1;
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while (!reg_ready) @(posedge clk);
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@(posedge clk);
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reg_valid = 1'b0;
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end
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endtask
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// ============================================================
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// M10+ real cycle-accounting instrumentation (testbench-only, no
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// RTL touched -- same idiom as EXP-0013).
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// ============================================================
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reg measure_en;
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integer total_cycles;
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integer psram_busy_cycles;
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genvar gi;
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reg [N_SLOTS_CFG-1:0] slot_busy_bit; // memory_manager.state != MM_IDLE, this cycle
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reg [N_SLOTS_CFG-1:0] slot_tile_bit; // operand_valid && operand_ready, this cycle
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integer slot_busy_cycles [0:N_SLOTS_CFG-1];
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integer slot_tiles_delivered [0:N_SLOTS_CFG-1];
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generate
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for (gi = 0; gi < N_SLOTS_CFG; gi = gi + 1) begin : GEN_SLOT_MON
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always @(*) begin
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slot_busy_bit[gi] = (u_nmp.u_dataflow_core.GEN_SLOT[gi].u_mm.state != 3'd0);
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slot_tile_bit[gi] = u_nmp.u_dataflow_core.GEN_SLOT[gi].mm_operand_valid &&
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u_nmp.u_dataflow_core.GEN_SLOT[gi].mm_operand_ready;
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end
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end
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endgenerate
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// Director/dependency bookkeeping
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integer jobs_allocated, jobs_completed, wakeups;
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integer waiting_sum, ready_sum, dispatched_sum, sample_count;
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integer ni;
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// Occupancy sampling is EXPENSIVE (a full N_NODES=512 scan) and is
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// only needed for the small/structural workloads (A/B/E/F), not
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// for the large neuron counts (C/D) where it would dominate
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// simulation wall-time for no real benefit (per-slot/PSRAM/tile
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// counters below are cheap and always collected). Gated by
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// sample_occupancy, set per-workload.
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reg sample_occupancy;
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integer scan_i;
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integer waiting_now, ready_now, dispatched_now;
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always @(posedge clk) begin
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if (measure_en) begin
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total_cycles <= total_cycles + 1;
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if (u_nmp.u_arbiter.owner != 0) psram_busy_cycles <= psram_busy_cycles + 1;
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for (ni = 0; ni < N_SLOTS_CFG; ni = ni + 1) begin
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if (slot_busy_bit[ni]) slot_busy_cycles[ni] <= slot_busy_cycles[ni] + 1;
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if (slot_tile_bit[ni]) slot_tiles_delivered[ni] <= slot_tiles_delivered[ni] + 1;
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end
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if (u_nmp.u_dataflow_core.dm_ready_valid && u_nmp.u_dataflow_core.dm_ready_ready)
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jobs_allocated <= jobs_allocated + 1;
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if (u_nmp.u_dataflow_core.dir_job_out_done)
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jobs_completed <= jobs_completed + 1;
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if (u_nmp.u_dataflow_core.dm_producer_done_valid)
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wakeups <= wakeups + 1;
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if (sample_occupancy) begin
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waiting_now = 0; ready_now = 0; dispatched_now = 0;
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for (scan_i = 0; scan_i < N_NODES; scan_i = scan_i + 1) begin
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case (u_nmp.u_dataflow_core.u_dep_mgr.node_state[scan_i])
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2'd1: waiting_now = waiting_now + 1;
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2'd2: ready_now = ready_now + 1;
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2'd3: dispatched_now = dispatched_now + 1;
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default: ;
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endcase
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end
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waiting_sum <= waiting_sum + waiting_now;
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ready_sum <= ready_sum + ready_now;
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dispatched_sum <= dispatched_sum + dispatched_now;
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sample_count <= sample_count + 1;
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end
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end
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end
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task automatic reset_instrumentation(input do_sample_occupancy);
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integer k;
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begin
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total_cycles = 0; psram_busy_cycles = 0;
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jobs_allocated = 0; jobs_completed = 0; wakeups = 0;
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waiting_sum = 0; ready_sum = 0; dispatched_sum = 0; sample_count = 0;
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sample_occupancy = do_sample_occupancy;
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for (k = 0; k < N_SLOTS_CFG; k = k + 1) begin
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slot_busy_cycles[k] = 0;
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slot_tiles_delivered[k] = 0;
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end
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end
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endtask
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task automatic report_instrumentation(input [255:0] label, input integer n_neurons_completed);
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integer k, total_tiles;
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real avg_waiting, avg_ready, avg_dispatched;
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real psram_util, sustained_mac_per_cycle, wallclock_us;
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begin
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total_tiles = 0;
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for (k = 0; k < N_SLOTS_CFG; k = k + 1) total_tiles = total_tiles + slot_tiles_delivered[k];
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avg_waiting = (sample_count > 0) ? (1.0*waiting_sum/sample_count) : 0.0;
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avg_ready = (sample_count > 0) ? (1.0*ready_sum/sample_count) : 0.0;
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avg_dispatched = (sample_count > 0) ? (1.0*dispatched_sum/sample_count) : 0.0;
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psram_util = (total_cycles > 0) ? (100.0*psram_busy_cycles/total_cycles) : 0.0;
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sustained_mac_per_cycle = (total_cycles > 0) ? (1.0*total_tiles*P_IN/total_cycles) : 0.0;
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wallclock_us = total_cycles * CLK_PERIOD / 1000.0;
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$display("---- BENCHMARK REPORT: %0s ----", label);
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$display(" total_cycles=%0d wallclock_us=%0.3f", total_cycles, wallclock_us);
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$display(" neurons_completed=%0d tiles_delivered(real)=%0d", n_neurons_completed, total_tiles);
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$display(" jobs_allocated=%0d jobs_completed=%0d dependency_wakeups=%0d", jobs_allocated, jobs_completed, wakeups);
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$display(" shared PSRAM port utilization: %0.1f%% (%0d/%0d busy cycles)", psram_util, psram_busy_cycles, total_cycles);
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for (k = 0; k < N_SLOTS_CFG; k = k + 1)
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$display(" slot %0d: busy=%0d/%0d (%0.1f%%) tiles=%0d", k, slot_busy_cycles[k], total_cycles,
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(total_cycles>0)?(100.0*slot_busy_cycles[k]/total_cycles):0.0, slot_tiles_delivered[k]);
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if (sample_count > 0)
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$display(" dependency_manager avg occupancy (sampled every measured cycle): waiting=%0.2f ready=%0.2f dispatched=%0.2f", avg_waiting, avg_ready, avg_dispatched);
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else
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$display(" dependency_manager occupancy: NOT SAMPLED for this workload (N_NODES scan skipped for large neuron counts to keep simulation time reasonable)");
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$display(" DERIVED: sustained end-to-end MAC/cycle = %0.4f (real tiles*%0d / real total_cycles)", sustained_mac_per_cycle, P_IN);
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if (n_neurons_completed > 0)
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$display(" DERIVED: cycles/neuron = %0.2f", 1.0*total_cycles/n_neurons_completed);
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if (total_tiles > 0)
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$display(" DERIVED: cycles/tile = %0.2f", 1.0*total_cycles/total_tiles);
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end
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endtask
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// ============================================================
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// Workload generators
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// ============================================================
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integer errors, tests;
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integer wd;
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// A/B/C/D: shared-input dense layer. Generates the shared X
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// vector, then N independent (neuron, weight-vector) jobs, each
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// verified bit-exact against the golden model.
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task automatic run_dense_layer(
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input [255:0] label,
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input integer n_neurons,
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input integer n_tiles_count,
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input [NODE_IDW-1:0] node_base,
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input [ADDR_WIDTH-1:0] x_base,
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input [ADDR_WIDTH-1:0] w_base,
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input [ADDR_WIDTH-1:0] res_base,
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input sample_occ
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);
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integer n, t, k, len, acc;
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reg signed [7:0] xv, wv, golden, real_y;
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reg [MAX_DEPS*NODE_IDW-1:0] no_deps;
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integer completed, wd2;
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begin
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len = n_tiles_count * P_IN;
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no_deps = {(MAX_DEPS*NODE_IDW){1'b0}};
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// shared input vector
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for (k = 0; k < len; k = k + 1)
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poke_byte(x_base + k, ((k % 8) + 1));
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reset_instrumentation(sample_occ);
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measure_en = 1'b1;
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for (n = 0; n < n_neurons; n = n + 1) begin
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acc = 0;
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for (t = 0; t < n_tiles_count; t = t + 1) begin
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for (k = 0; k < P_IN; k = k + 1) begin
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xv = peek_byte(x_base + t*P_IN + k);
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wv = (((n + t*P_IN + k) % 8) + 1);
|
|
poke_byte(w_base + n*len + t*P_IN + k, wv);
|
|
acc = acc + xv*wv;
|
|
end
|
|
end
|
|
golden = relu_sat(acc);
|
|
poke_byte(res_base + n, 8'sd0); // poison, must NOT still be 0 after completion (unless golden IS 0 -- checked separately)
|
|
register_node(node_base + n[NODE_IDW-1:0], 0, no_deps,
|
|
x_base, w_base + n*len, n_tiles_count[15:0], res_base + n);
|
|
if ((n % 32) == 0) begin
|
|
$display(" [%0s] registered %0d/%0d", label, n+1, n_neurons);
|
|
$fflush;
|
|
end
|
|
end
|
|
$display(" [%0s] all %0d neurons registered, waiting for completion...", label, n_neurons);
|
|
$fflush;
|
|
|
|
// wait for all n_neurons completions
|
|
completed = 0; wd2 = 0;
|
|
while (completed < n_neurons && wd2 < 2000000) begin
|
|
@(posedge clk);
|
|
wd2 = wd2 + 1;
|
|
completed = jobs_completed;
|
|
if ((wd2 % 20000) == 0) begin
|
|
$display(" [%0s] watchdog %0d: completed=%0d/%0d total_cycles=%0d", label, wd2, completed, n_neurons, total_cycles);
|
|
$fflush;
|
|
end
|
|
end
|
|
repeat(5) @(posedge clk);
|
|
measure_en = 1'b0;
|
|
|
|
tests = tests + 1;
|
|
if (completed < n_neurons) begin
|
|
$display("FAIL %0s: only %0d/%0d neurons completed within watchdog", label, completed, n_neurons);
|
|
errors = errors + 1;
|
|
end else begin : check_block
|
|
integer local_errors;
|
|
local_errors = 0;
|
|
for (n = 0; n < n_neurons; n = n + 1) begin
|
|
acc = 0;
|
|
for (t = 0; t < n_tiles_count; t = t + 1)
|
|
for (k = 0; k < P_IN; k = k + 1)
|
|
acc = acc + peek_byte(x_base + t*P_IN + k) * peek_byte(w_base + n*len + t*P_IN + k);
|
|
golden = relu_sat(acc);
|
|
real_y = peek_byte(res_base + n);
|
|
if (real_y !== golden) begin
|
|
$display("FAIL %0s neuron %0d: real=%0d golden=%0d", label, n, real_y, golden);
|
|
local_errors = local_errors + 1;
|
|
end
|
|
end
|
|
if (local_errors == 0)
|
|
$display("PASS %0s: all %0d neurons bit-exact vs golden", label, n_neurons);
|
|
else
|
|
errors = errors + 1;
|
|
end
|
|
report_instrumentation(label, n_neurons);
|
|
end
|
|
endtask
|
|
|
|
// E: Multilayer (8 layer-1 random neurons -> shared hidden vector
|
|
// -> 2 layer-2 neurons consuming it, real dependency wake-up +
|
|
// real cross-node data forwarding through real PSRAM).
|
|
localparam L1_N = 8;
|
|
localparam L2_N = 2;
|
|
integer rand_seed;
|
|
|
|
task automatic run_multilayer(
|
|
input [NODE_IDW-1:0] node_base,
|
|
input [ADDR_WIDTH-1:0] l1x_base, input [ADDR_WIDTH-1:0] l1w_base,
|
|
input [ADDR_WIDTH-1:0] hidden_base,
|
|
input [ADDR_WIDTH-1:0] l2w_base, input [ADDR_WIDTH-1:0] l2res_base
|
|
);
|
|
integer n, k, acc, completed, wd2;
|
|
reg signed [7:0] xv, wv, golden_l1 [0:L1_N-1], golden_l2, real_y;
|
|
reg [MAX_DEPS*NODE_IDW-1:0] no_deps, l2_deps;
|
|
integer local_errors;
|
|
begin
|
|
no_deps = {(MAX_DEPS*NODE_IDW){1'b0}};
|
|
l2_deps = {(MAX_DEPS*NODE_IDW){1'b0}};
|
|
for (n = 0; n < L1_N; n = n + 1)
|
|
l2_deps[n*NODE_IDW +: NODE_IDW] = node_base + n[NODE_IDW-1:0];
|
|
|
|
rand_seed = 32'hC0FFEE01;
|
|
$display("RANDOM SEED (workload E, layer-1 data) = 32'h%08h", rand_seed);
|
|
|
|
reset_instrumentation(1'b1);
|
|
measure_en = 1'b1;
|
|
|
|
for (n = 0; n < L1_N; n = n + 1) begin
|
|
acc = 0;
|
|
for (k = 0; k < P_IN; k = k + 1) begin
|
|
xv = $random(rand_seed) % 9; // deterministic PRNG stream, range roughly [-8,8]
|
|
wv = $random(rand_seed) % 9;
|
|
poke_byte(l1x_base + n*P_IN + k, xv);
|
|
poke_byte(l1w_base + n*P_IN + k, wv);
|
|
acc = acc + xv*wv;
|
|
end
|
|
golden_l1[n] = relu_sat(acc);
|
|
poke_byte(hidden_base + n, 8'sd0); // poison hidden slot
|
|
register_node(node_base + n[NODE_IDW-1:0], 0, no_deps,
|
|
l1x_base + n*P_IN, l1w_base + n*P_IN, 16'd1, hidden_base + n);
|
|
end
|
|
|
|
for (n = 0; n < L2_N; n = n + 1) begin
|
|
for (k = 0; k < P_IN; k = k + 1)
|
|
poke_byte(l2w_base + n*P_IN + k, ((n + k) % 6) + 1);
|
|
register_node(node_base + L1_N[NODE_IDW-1:0] + n[NODE_IDW-1:0], L1_N[$clog2(MAX_DEPS+1)-1:0], l2_deps,
|
|
hidden_base, l2w_base + n*P_IN, 16'd1, l2res_base + n);
|
|
end
|
|
|
|
completed = 0; wd2 = 0;
|
|
while (completed < (L1_N+L2_N) && wd2 < 2000000) begin
|
|
@(posedge clk); wd2 = wd2 + 1; completed = jobs_completed;
|
|
end
|
|
repeat(5) @(posedge clk);
|
|
measure_en = 1'b0;
|
|
|
|
tests = tests + 1;
|
|
local_errors = 0;
|
|
if (completed < (L1_N+L2_N)) begin
|
|
$display("FAIL Multilayer: only %0d/%0d nodes completed", completed, L1_N+L2_N);
|
|
local_errors = local_errors + 1;
|
|
end else begin
|
|
for (n = 0; n < L1_N; n = n + 1) begin
|
|
real_y = peek_byte(hidden_base + n);
|
|
if (real_y !== golden_l1[n]) begin
|
|
$display("FAIL Multilayer L1 neuron %0d: real=%0d golden=%0d", n, real_y, golden_l1[n]);
|
|
local_errors = local_errors + 1;
|
|
end
|
|
end
|
|
for (n = 0; n < L2_N; n = n + 1) begin
|
|
acc = 0;
|
|
for (k = 0; k < P_IN; k = k + 1)
|
|
acc = acc + golden_l1[k] * peek_byte(l2w_base + n*P_IN + k);
|
|
golden_l2 = relu_sat(acc);
|
|
real_y = peek_byte(l2res_base + n);
|
|
if (real_y !== golden_l2) begin
|
|
$display("FAIL Multilayer L2 neuron %0d: real=%0d golden=%0d (using REAL L1 hidden values)", n, real_y, golden_l2);
|
|
local_errors = local_errors + 1;
|
|
end
|
|
end
|
|
end
|
|
if (local_errors == 0) $display("PASS Multilayer: 8 L1 (random) -> 2 L2 neurons, all bit-exact, real cross-node forwarding via real PSRAM");
|
|
else errors = errors + 1;
|
|
report_instrumentation("E-Multilayer", L1_N+L2_N);
|
|
end
|
|
endtask
|
|
|
|
// F: DAG diamond+fan-in (A,B indep; C dep-A; D dep-B; E dep-C&D
|
|
// [2-hop]; F dep-A,B,C [mixed, 3 producers])
|
|
task automatic run_dag(
|
|
input [NODE_IDW-1:0] node_base,
|
|
input [ADDR_WIDTH-1:0] x_base, input [ADDR_WIDTH-1:0] w_base, input [ADDR_WIDTH-1:0] res_base
|
|
);
|
|
integer n, k, acc, completed, wd2, local_errors;
|
|
reg signed [7:0] golden [0:5];
|
|
reg signed [7:0] real_y;
|
|
reg [MAX_DEPS*NODE_IDW-1:0] deps;
|
|
reg [NODE_IDW-1:0] idA, idB, idC, idD, idE, idF;
|
|
begin
|
|
idA = node_base+0; idB = node_base+1; idC = node_base+2;
|
|
idD = node_base+3; idE = node_base+4; idF = node_base+5;
|
|
|
|
// Each of the 6 nodes: its own small independent 8-input
|
|
// job (deterministic, distinct per node) -- dependencies
|
|
// here are purely about SCHEDULING/wake-up order, not
|
|
// data forwarding (workload E already covers that).
|
|
for (n = 0; n < 6; n = n + 1) begin
|
|
acc = 0;
|
|
for (k = 0; k < P_IN; k = k + 1) begin
|
|
poke_byte(x_base + n*P_IN + k, ((n+k)%4)+1);
|
|
poke_byte(w_base + n*P_IN + k, ((n+k)%5)+1);
|
|
acc = acc + peek_byte(x_base+n*P_IN+k)*peek_byte(w_base+n*P_IN+k);
|
|
end
|
|
golden[n] = relu_sat(acc);
|
|
poke_byte(res_base + n, 8'sd0);
|
|
end
|
|
|
|
reset_instrumentation(1'b1);
|
|
measure_en = 1'b1;
|
|
|
|
deps = {(MAX_DEPS*NODE_IDW){1'b0}};
|
|
register_node(idA, 0, deps, x_base+0*P_IN, w_base+0*P_IN, 16'd1, res_base+0);
|
|
register_node(idB, 0, deps, x_base+1*P_IN, w_base+1*P_IN, 16'd1, res_base+1);
|
|
|
|
deps = {(MAX_DEPS*NODE_IDW){1'b0}}; deps[0*NODE_IDW+:NODE_IDW] = idA;
|
|
register_node(idC, 1, deps, x_base+2*P_IN, w_base+2*P_IN, 16'd1, res_base+2);
|
|
|
|
deps = {(MAX_DEPS*NODE_IDW){1'b0}}; deps[0*NODE_IDW+:NODE_IDW] = idB;
|
|
register_node(idD, 1, deps, x_base+3*P_IN, w_base+3*P_IN, 16'd1, res_base+3);
|
|
|
|
deps = {(MAX_DEPS*NODE_IDW){1'b0}}; deps[0*NODE_IDW+:NODE_IDW] = idC; deps[1*NODE_IDW+:NODE_IDW] = idD;
|
|
register_node(idE, 2, deps, x_base+4*P_IN, w_base+4*P_IN, 16'd1, res_base+4);
|
|
|
|
deps = {(MAX_DEPS*NODE_IDW){1'b0}}; deps[0*NODE_IDW+:NODE_IDW] = idA; deps[1*NODE_IDW+:NODE_IDW] = idB; deps[2*NODE_IDW+:NODE_IDW] = idC;
|
|
register_node(idF, 3, deps, x_base+5*P_IN, w_base+5*P_IN, 16'd1, res_base+5);
|
|
|
|
completed = 0; wd2 = 0;
|
|
while (completed < 6 && wd2 < 2000000) begin @(posedge clk); wd2=wd2+1; completed = jobs_completed; end
|
|
repeat(5) @(posedge clk);
|
|
measure_en = 1'b0;
|
|
|
|
tests = tests + 1;
|
|
local_errors = 0;
|
|
if (completed < 6) begin
|
|
$display("FAIL DAG: only %0d/6 nodes completed", completed);
|
|
local_errors = local_errors + 1;
|
|
end else begin
|
|
for (n = 0; n < 6; n = n + 1) begin
|
|
real_y = peek_byte(res_base+n);
|
|
if (real_y !== golden[n]) begin
|
|
$display("FAIL DAG node %0d: real=%0d golden=%0d", n, real_y, golden[n]);
|
|
local_errors = local_errors + 1;
|
|
end
|
|
end
|
|
end
|
|
if (local_errors == 0) $display("PASS DAG: 6-node diamond+fan-in (2-hop transitive wake-up, 3-producer mixed-depth dependency), all bit-exact");
|
|
else errors = errors + 1;
|
|
report_instrumentation("F-DAG", 6);
|
|
end
|
|
endtask
|
|
|
|
initial begin
|
|
errors = 0; tests = 0;
|
|
rst = 1; reg_valid = 0; reg_node_id = 0; reg_required = 0; reg_producer_ids = 0;
|
|
reg_x_base = 0; reg_w_base = 0; reg_n_tiles = 0; reg_result_addr = 0;
|
|
measure_en = 0;
|
|
repeat(5) @(posedge clk);
|
|
rst = 0;
|
|
|
|
$display("========================================");
|
|
$display("FPGA-Neural V2 Final Benchmark Campaign -- N_SLOTS_CFG=%0d", N_SLOTS_CFG);
|
|
$display("========================================");
|
|
|
|
wait (u_nmp.u_psram_ctrl.state == u_nmp.u_psram_ctrl.STATE_IDLE);
|
|
@(posedge clk);
|
|
|
|
run_dense_layer("A-Small", 16, 1, 16'd0, 23'h001000, 23'h002000, 23'h003000, 1'b1);
|
|
run_dense_layer("B-Medium", 64, 4, 16'd100, 23'h010000, 23'h011000, 23'h018000, 1'b1);
|
|
run_dense_layer("C-Large", 128, 16, 16'd200, 23'h030000, 23'h031000, 23'h048000, 1'b0);
|
|
run_dense_layer("D-Stress", 256, 16, 16'd400, 23'h060000, 23'h062000, 23'h090000, 1'b0);
|
|
run_multilayer(16'd700, 23'h0A0000, 23'h0A1000, 23'h0A2000, 23'h0A3000, 23'h0A4000);
|
|
run_dag(16'd800, 23'h0B0000, 23'h0B1000, 23'h0B2000);
|
|
|
|
$display("========================================");
|
|
if (errors == 0)
|
|
$display("ALL %0d WORKLOAD SUITES PASSED (N_SLOTS_CFG=%0d, real V1 PSRAM chain, real slot_mem_arbiter)", tests, N_SLOTS_CFG);
|
|
else
|
|
$display("FAILED: %0d/%0d workload suite(s) had errors -- see messages above", errors, tests);
|
|
$display("========================================");
|
|
$finish;
|
|
end
|
|
|
|
endmodule
|