p-j-r-1-2-3 commited on
Commit
e9c58b6
·
verified ·
1 Parent(s): 9c20c0d

add run default

Browse files
applied/opt08_mint_quant/default.summary.json ADDED
@@ -0,0 +1,276 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "key": "opt08_mint_quant/default",
3
+ "tag": "default",
4
+ "script": "opt08_mint_quant.py",
5
+ "script_sha256_16": "dd139bbe634ea732",
6
+ "hf_folder": "applied/opt08_mint_quant",
7
+ "priority": 0,
8
+ "note": "default: w-bits=4, u-bits=2",
9
+ "phase": 2,
10
+ "n_phases": 10,
11
+ "method": "harmonic_matched",
12
+ "command": [
13
+ "/usr/bin/python3",
14
+ "-m",
15
+ "torch.distributed.run",
16
+ "--standalone",
17
+ "--nproc_per_node=2",
18
+ "/kaggle/working/scripts/opt08_mint_quant.py",
19
+ "--method",
20
+ "harmonic_matched",
21
+ "--data-root",
22
+ "/kaggle/working/data",
23
+ "--epochs",
24
+ "60",
25
+ "--seed",
26
+ "1234",
27
+ "--batch-size",
28
+ "64",
29
+ "--event-eval",
30
+ "--no-resume",
31
+ "--decision-margin",
32
+ "2.0",
33
+ "--hub-dir",
34
+ "/kaggle/working/hub/opt08_mint_quant/default",
35
+ "--keep-epoch-weights",
36
+ "1",
37
+ "--resplit",
38
+ "block",
39
+ "--drop-rest",
40
+ "--bench"
41
+ ],
42
+ "flags": [],
43
+ "epochs_requested": 60,
44
+ "gpus": 2,
45
+ "relative_epoch_cost": 1.0,
46
+ "exit_code": 0,
47
+ "status": "ok",
48
+ "duration_s": 325.4,
49
+ "started_utc": "2026-08-23T04:32:39.206762+00:00",
50
+ "finished_utc": "2026-08-23T04:38:04.595226+00:00",
51
+ "optimization_summary": {
52
+ "optimization": "mint_quant",
53
+ "research_section": "4. Membrane-Potential Memory-Wall Optimizations (multiplier-less integer quantization)",
54
+ "reference": "Yin et al., MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks, arXiv:2305.09850 (ASP-DAC 2024)",
55
+ "script": "opt08_mint_quant.py",
56
+ "baseline_mode": false,
57
+ "method": "harmonic_matched",
58
+ "accuracy": {
59
+ "test_acc": 0.24714285714285714,
60
+ "test_target_acc": 0.24714285714285714,
61
+ "best_val_acc": 0.5085714285714286
62
+ },
63
+ "efficiency": {
64
+ "spikes_per_inference": null,
65
+ "syn_ops_per_inference": 850625.0412946428,
66
+ "dense_macs_per_inference": 122675200.0,
67
+ "event_fraction_of_dense": 0.006933960908925707,
68
+ "syn_ops_per_inference_dense_fanout": 63614042.63717532,
69
+ "weight_sparsity": 0.9790471097662772,
70
+ "effective_ticks": 39.044285714285714,
71
+ "num_ticks": 100,
72
+ "membrane_bytes_per_inference": 0,
73
+ "weight_bytes": 613376,
74
+ "input_raster_bytes": null,
75
+ "train_ms_per_step": 89.64440669997202,
76
+ "infer_ms_per_sample": 0.6133386103124394,
77
+ "peak_vram_mb": 2834.896384
78
+ },
79
+ "optimization_specific": {
80
+ "w_bits": 4,
81
+ "u_bits": 2,
82
+ "leak_shift": 0,
83
+ "beta_eff": 1.0,
84
+ "qat": true,
85
+ "batchnorm": true,
86
+ "membrane_memory_reduction_x": 16.0,
87
+ "weight_memory_reduction_x": 8.0,
88
+ "membrane_bytes_per_inference": 28200.0,
89
+ "working_set_bytes": 613658.0,
90
+ "baseline_working_set_bytes": 4911520.0,
91
+ "l2_cache_fits": true,
92
+ "baseline_l2_cache_fits": false,
93
+ "l2_budget_bytes": 2097152,
94
+ "membrane_saturation_frac": 0.019412504155585104,
95
+ "acc_vs_ubits": {
96
+ "2": 0.24714285714285714,
97
+ "4": 0.22214285714285714,
98
+ "8": 0.23285714285714285,
99
+ "0": 0.18928571428571428
100
+ },
101
+ "bits_sweep_rows": [
102
+ {
103
+ "u_bits": 2,
104
+ "acc": 0.24714285714285714,
105
+ "target_acc": 0.24714285714285714,
106
+ "membrane_bytes_per_neuron_per_tick": 0.25,
107
+ "membrane_memory_reduction_x": 16.0,
108
+ "membrane_saturation_frac": 0.017122742132092198,
109
+ "acc_drop_vs_fp32": -0.05785714285714286
110
+ },
111
+ {
112
+ "u_bits": 4,
113
+ "acc": 0.22214285714285714,
114
+ "target_acc": 0.22214285714285714,
115
+ "membrane_bytes_per_neuron_per_tick": 0.5,
116
+ "membrane_memory_reduction_x": 8.0,
117
+ "membrane_saturation_frac": 0.16233945589539006,
118
+ "acc_drop_vs_fp32": -0.03285714285714286
119
+ },
120
+ {
121
+ "u_bits": 8,
122
+ "acc": 0.23285714285714285,
123
+ "target_acc": 0.23285714285714285,
124
+ "membrane_bytes_per_neuron_per_tick": 1.0,
125
+ "membrane_memory_reduction_x": 4.0,
126
+ "membrane_saturation_frac": 0.36418647495567374,
127
+ "acc_drop_vs_fp32": -0.043571428571428567
128
+ },
129
+ {
130
+ "u_bits": 0,
131
+ "acc": 0.18928571428571428,
132
+ "target_acc": 0.18928571428571428,
133
+ "membrane_bytes_per_neuron_per_tick": 4.0,
134
+ "membrane_memory_reduction_x": 1.0,
135
+ "membrane_saturation_frac": null,
136
+ "acc_drop_vs_fp32": 0.0
137
+ }
138
+ ],
139
+ "fp32_membrane_acc": 0.18928571428571428,
140
+ "per_layer_scales": [
141
+ {
142
+ "layer": 0,
143
+ "weight_scale": 0.026102902633803233,
144
+ "membrane_scale": 1.0,
145
+ "shared_scale_gauge_factor": 38.30991572197802
146
+ },
147
+ {
148
+ "layer": 1,
149
+ "weight_scale": 0.02913376901830946,
150
+ "membrane_scale": 1.0,
151
+ "shared_scale_gauge_factor": 34.324429474660086
152
+ },
153
+ {
154
+ "layer": 2,
155
+ "weight_scale": 0.028474173375538418,
156
+ "membrane_scale": 1.0,
157
+ "shared_scale_gauge_factor": 35.11954453642119
158
+ },
159
+ {
160
+ "layer": 3,
161
+ "weight_scale": 0.0215481093951634,
162
+ "membrane_scale": 1.0,
163
+ "shared_scale_gauge_factor": 46.40778370210316
164
+ }
165
+ ],
166
+ "shared_scale_note": "weight grid and membrane grid are the same grid up to a per-layer positive scalar that BatchNorm absorbs exactly; exact only with --batchnorm on",
167
+ "multiplier_less_compare": true,
168
+ "wall_clock_caveat": "this reference kernel computes in fp32 registers, so the traffic win does not appear in train_ms_per_step; a fixed-point core is where it becomes energy"
169
+ },
170
+ "config": {
171
+ "method": "harmonic_matched",
172
+ "data_root": "/kaggle/working/data",
173
+ "subjects": "",
174
+ "blocks": "",
175
+ "limit": 0,
176
+ "drop_rest": true,
177
+ "resplit": "block",
178
+ "test_blocks": "6",
179
+ "class_weight": false,
180
+ "epochs": 60,
181
+ "batch_size": 64,
182
+ "lr": 0.002,
183
+ "weight_decay": 0.0005,
184
+ "grad_clip": 5.0,
185
+ "num_bins": 100,
186
+ "window_sec": 5.0,
187
+ "hidden": "512,256",
188
+ "freq_groups": 8,
189
+ "dropout": 0.3,
190
+ "spike_drop": 0.1,
191
+ "time_jitter": 2,
192
+ "label_smoothing": 0.05,
193
+ "no_batchnorm": false,
194
+ "binary_input": false,
195
+ "beta": 1.0,
196
+ "thresh": 1.0,
197
+ "window": 0.5,
198
+ "gain": 1.0,
199
+ "alpha": 0.9,
200
+ "readout": "spikecount",
201
+ "fake_quant": 0,
202
+ "amp": false,
203
+ "spike_reg": 0.0,
204
+ "event_eval": true,
205
+ "decision_margin": 2.0,
206
+ "export": false,
207
+ "seed": 1234,
208
+ "hub_dir": "/kaggle/working/hub/opt08_mint_quant/default",
209
+ "repo_id": "UWU-R-13/SSVEP-SNN",
210
+ "push_hf": false,
211
+ "keep_epoch_weights": 1,
212
+ "no_resume": true,
213
+ "selftest": false,
214
+ "baseline": false,
215
+ "bench": true,
216
+ "bench_warmup": 10,
217
+ "bench_iters": 50,
218
+ "bench_train_steps": 20,
219
+ "w_bits": 4,
220
+ "u_bits": 2,
221
+ "leak_shift": 0,
222
+ "qat": true,
223
+ "bits_sweep": "2,4,8,0",
224
+ "l2_bytes": 2097152,
225
+ "sampling_rate": 250.0
226
+ }
227
+ },
228
+ "final_summary": {
229
+ "final_test_acc": 0.24714285714285714,
230
+ "final_test_target_acc": 0.24714285714285714,
231
+ "final_test_rest_recall": NaN,
232
+ "best_acc": 0.5085714285714286,
233
+ "best_epoch": 5,
234
+ "resplit": "block",
235
+ "class_weight": false,
236
+ "drop_rest": true,
237
+ "epochs": 60,
238
+ "method": "harmonic_matched",
239
+ "n_in": 2880,
240
+ "n_classes": 40,
241
+ "num_bins": 100
242
+ },
243
+ "event_driven_summary": {
244
+ "acc": 0.24714285714285714,
245
+ "anytime_acc": {
246
+ "0.25": 0.115,
247
+ "0.5": 0.17,
248
+ "0.75": 0.20785714285714285,
249
+ "1.0": 0.24714285714285714
250
+ },
251
+ "syn_per_inference": 850625.0412946428,
252
+ "dense_per_inference": 122675200.0,
253
+ "event_fraction_of_dense": 0.006933960908925707,
254
+ "syn_per_inference_dense_fanout": 63614042.63717532,
255
+ "weight_sparsity": 0.9790471097662772,
256
+ "num_ticks": 100,
257
+ "dt_ms": 50.0,
258
+ "margin_decision_acc": 0.13857142857142857,
259
+ "mean_decision_tick": 39.044285714285714,
260
+ "mean_decision_ms": 1952.2142857142858,
261
+ "dense_forward_test_acc": 0.24714285714285714
262
+ },
263
+ "extra_sweep_file_present": true,
264
+ "selftest": {
265
+ "mode": "gate",
266
+ "passed": true
267
+ },
268
+ "driver_version": 1,
269
+ "zip": {
270
+ "name": "default.zip",
271
+ "files": 81,
272
+ "bytes": 12351757,
273
+ "MB": 12.4,
274
+ "sha256": "c2ec90c788101866da3bd41fbc98fc8613354d1e1195170654ec755e22af7703"
275
+ }
276
+ }
applied/opt08_mint_quant/default.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c2ec90c788101866da3bd41fbc98fc8613354d1e1195170654ec755e22af7703
3
+ size 12351757