File size: 4,047 Bytes
e4cdd5f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | """Simulator vs Chip Comparison Benchmark
==========================================
Demonstrates both backends with the same network, comparing spike counts.
When no FPGA is connected, runs simulator-only and shows expected chip commands.
Features demonstrated: Backend abstraction, deploy/inject/run API, RunResult.
"""
import sys, os, time
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import neurocore as nc
from neurocore.compiler import Compiler
def build_network():
"""Build a moderately complex E/I network."""
net = nc.Network()
exc = net.population(64, params={
"threshold": 800, "leak": 5, "refrac": 3,
}, label="excitatory")
inh = net.population(16, params={
"threshold": 600, "leak": 2, "refrac": 2,
}, label="inhibitory")
net.connect(exc, exc, topology="random_sparse", p=0.1, weight=200, seed=42)
net.connect(exc, inh, topology="all_to_all", weight=150)
net.connect(inh, exc, topology="all_to_all", weight=-300, compartment=0)
return net, exc, inh
def run_simulator(net, exc, inh, timesteps=100):
"""Run on the software simulator."""
sim = nc.Simulator()
sim.deploy(net)
# Inject stimulus to first 8 excitatory neurons
sim.inject(exc[:8], current=1200)
result = sim.run(timesteps)
return result
def main():
print("=" * 60)
print(" Simulator vs Chip Comparison Benchmark")
print("=" * 60)
net, exc, inh = build_network()
timesteps = 100
# Compile and show network summary
compiled = Compiler().compile(net)
print(f"\nNetwork: {net.total_neurons()} neurons "
f"({net.populations[0].size} exc + {net.populations[1].size} inh)")
print(f"Compiled: {compiled.summary()}")
# Run simulator
print(f"\n--- Simulator ({timesteps} timesteps) ---")
t0 = time.perf_counter()
result = run_simulator(net, exc, inh, timesteps)
elapsed = time.perf_counter() - t0
print(f"Total spikes: {result.total_spikes}")
print(f"Active neurons: {len(result.spike_trains)}/{net.total_neurons()}")
print(f"Elapsed: {elapsed * 1000:.1f}ms")
rates = result.firing_rates()
if rates:
max_rate = max(rates.values())
avg_rate = sum(rates.values()) / len(rates)
print(f"Max firing rate: {max_rate:.2f} Hz")
print(f"Avg firing rate: {avg_rate:.2f} Hz (active neurons only)")
timeseries = result.spike_count_timeseries()
peak_t = max(range(len(timeseries)), key=lambda i: timeseries[i])
print(f"Peak activity: timestep {peak_t} ({timeseries[peak_t]} spikes)")
# Show what would be sent to FPGA
print(f"\n--- Chip Commands (would be sent via UART) ---")
print(f"PROG_NEURON commands: {len(compiled.prog_neuron_cmds)}")
print(f"PROG_INDEX commands: {len(compiled.prog_index_cmds)}")
print(f"PROG_POOL commands: {len(compiled.prog_pool_cmds)}")
print(f"PROG_ROUTE commands: {len(compiled.prog_route_cmds)}")
print(f"PROG_DELAY commands: {len(compiled.prog_delay_cmds)}")
total_bytes = (len(compiled.prog_neuron_cmds) * 7
+ len(compiled.prog_index_cmds) * 10
+ len(compiled.prog_pool_cmds) * 9
+ len(compiled.prog_route_cmds) * 10)
print(f"Total deploy payload: ~{total_bytes} bytes")
# Try chip backend (will fail without hardware)
print(f"\n--- Chip Backend ---")
try:
chip = nc.Chip(port="COM3")
chip.deploy(net)
chip.inject(exc[:8], current=1200)
chip_result = chip.run(timesteps)
print(f"Chip spikes: {chip_result.total_spikes}")
print(f"Match: {'YES' if chip_result.total_spikes == result.total_spikes else 'NO'}")
chip.close()
except Exception as e:
print(f"No FPGA connected ({type(e).__name__})")
print(" Run with --port <port> when FPGA is attached")
print("\nDone!")
if __name__ == "__main__":
main()
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