add run w_bits_2

applied/opt08_mint_quant/w_bits_2.summary.json

@@ -0,0 +1,281 @@
+{
+  "key": "opt08_mint_quant/w_bits_2",
+  "tag": "w_bits_2",
+  "script": "opt08_mint_quant.py",
+  "script_sha256_16": "dd139bbe634ea732",
+  "hf_folder": "applied/opt08_mint_quant",
+  "priority": 2,
+  "note": "most aggressive weight quantization",
+  "phase": 10,
+  "n_phases": 10,
+  "method": "harmonic_matched",
+  "command": [
+    "/usr/bin/python3",
+    "-m",
+    "torch.distributed.run",
+    "--standalone",
+    "--nproc_per_node=2",
+    "/kaggle/working/scripts/opt08_mint_quant.py",
+    "--method",
+    "harmonic_matched",
+    "--data-root",
+    "/kaggle/working/data",
+    "--epochs",
+    "60",
+    "--seed",
+    "1234",
+    "--batch-size",
+    "64",
+    "--event-eval",
+    "--no-resume",
+    "--decision-margin",
+    "2.0",
+    "--hub-dir",
+    "/kaggle/working/hub/opt08_mint_quant/w_bits_2",
+    "--keep-epoch-weights",
+    "1",
+    "--resplit",
+    "block",
+    "--drop-rest",
+    "--bench",
+    "--w-bits",
+    "2"
+  ],
+  "flags": [
+    "--w-bits",
+    "2"
+  ],
+  "epochs_requested": 60,
+  "gpus": 2,
+  "relative_epoch_cost": 1.0,
+  "exit_code": 0,
+  "status": "ok",
+  "duration_s": 313.7,
+  "started_utc": "2026-08-23T05:13:04.031271+00:00",
+  "finished_utc": "2026-08-23T05:18:17.741632+00:00",
+  "optimization_summary": {
+    "optimization": "mint_quant",
+    "research_section": "4. Membrane-Potential Memory-Wall Optimizations (multiplier-less integer quantization)",
+    "reference": "Yin et al., MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks, arXiv:2305.09850 (ASP-DAC 2024)",
+    "script": "opt08_mint_quant.py",
+    "baseline_mode": false,
+    "method": "harmonic_matched",
+    "accuracy": {
+      "test_acc": 0.03214285714285714,
+      "test_target_acc": 0.03214285714285714,
+      "best_val_acc": 0.23142857142857143
+    },
+    "efficiency": {
+      "spikes_per_inference": null,
+      "syn_ops_per_inference": 64874.41061282468,
+      "dense_macs_per_inference": 122675200.0,
+      "event_fraction_of_dense": 0.0005288306896000551,
+      "syn_ops_per_inference_dense_fanout": 63605566.99918831,
+      "weight_sparsity": 0.9991204416214524,
+      "effective_ticks": 84.10142857142857,
+      "num_ticks": 100,
+      "membrane_bytes_per_inference": 0,
+      "weight_bytes": 306688,
+      "input_raster_bytes": null,
+      "train_ms_per_step": 85.21973990000333,
+      "infer_ms_per_sample": 0.5962876021874308,
+      "peak_vram_mb": 2835.795968
+    },
+    "optimization_specific": {
+      "w_bits": 2,
+      "u_bits": 2,
+      "leak_shift": 0,
+      "beta_eff": 1.0,
+      "qat": true,
+      "batchnorm": true,
+      "membrane_memory_reduction_x": 16.0,
+      "weight_memory_reduction_x": 16.0,
+      "membrane_bytes_per_inference": 28200.0,
+      "working_set_bytes": 306970.0,
+      "baseline_working_set_bytes": 4911520.0,
+      "l2_cache_fits": true,
+      "baseline_l2_cache_fits": false,
+      "l2_budget_bytes": 2097152,
+      "membrane_saturation_frac": 0.008376689937943263,
+      "acc_vs_ubits": {
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+        "4": 0.03785714285714286,
+        "8": 0.03357142857142857,
+        "0": 0.03428571428571429
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+      "bits_sweep_rows": [
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+          "u_bits": 2,
+          "acc": 0.03214285714285714,
+          "target_acc": 0.03214285714285714,
+          "membrane_bytes_per_neuron_per_tick": 0.25,
+          "membrane_memory_reduction_x": 16.0,
+          "membrane_saturation_frac": 0.007398326684397164,
+          "acc_drop_vs_fp32": 0.0021428571428571477
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+        {
+          "u_bits": 4,
+          "acc": 0.03785714285714286,
+          "target_acc": 0.03785714285714286,
+          "membrane_bytes_per_neuron_per_tick": 0.5,
+          "membrane_memory_reduction_x": 8.0,
+          "membrane_saturation_frac": 0.05461069093528369,
+          "acc_drop_vs_fp32": -0.0035714285714285726
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+        {
+          "u_bits": 8,
+          "acc": 0.03357142857142857,
+          "target_acc": 0.03357142857142857,
+          "membrane_bytes_per_neuron_per_tick": 1.0,
+          "membrane_memory_reduction_x": 4.0,
+          "membrane_saturation_frac": 0.1291535073138298,
+          "acc_drop_vs_fp32": 0.0007142857142857159
+        },
+        {
+          "u_bits": 0,
+          "acc": 0.03428571428571429,
+          "target_acc": 0.03428571428571429,
+          "membrane_bytes_per_neuron_per_tick": 4.0,
+          "membrane_memory_reduction_x": 1.0,
+          "membrane_saturation_frac": null,
+          "acc_drop_vs_fp32": 0.0
+        }
+      ],
+      "fp32_membrane_acc": 0.03428571428571429,
+      "per_layer_scales": [
+        {
+          "layer": 0,
+          "weight_scale": 0.1566811352968216,
+          "membrane_scale": 1.0,
+          "shared_scale_gauge_factor": 6.382389290871355
+        },
+        {
+          "layer": 1,
+          "weight_scale": 0.1379482001066208,
+          "membrane_scale": 1.0,
+          "shared_scale_gauge_factor": 7.249097844169735
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+        {
+          "layer": 2,
+          "weight_scale": 0.07789017260074615,
+          "membrane_scale": 1.0,
+          "shared_scale_gauge_factor": 12.83859011490264
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+        {
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+          "weight_scale": 0.1205046996474266,
+          "membrane_scale": 1.0,
+          "shared_scale_gauge_factor": 8.298431537739242
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+      ],
+      "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",
+      "multiplier_less_compare": true,
+      "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"
+    },
+    "config": {
+      "method": "harmonic_matched",
+      "data_root": "/kaggle/working/data",
+      "subjects": "",
+      "blocks": "",
+      "limit": 0,
+      "drop_rest": true,
+      "resplit": "block",
+      "test_blocks": "6",
+      "class_weight": false,
+      "epochs": 60,
+      "batch_size": 64,
+      "lr": 0.002,
+      "weight_decay": 0.0005,
+      "grad_clip": 5.0,
+      "num_bins": 100,
+      "window_sec": 5.0,
+      "hidden": "512,256",
+      "freq_groups": 8,
+      "dropout": 0.3,
+      "spike_drop": 0.1,
+      "time_jitter": 2,
+      "label_smoothing": 0.05,
+      "no_batchnorm": false,
+      "binary_input": false,
+      "beta": 1.0,
+      "thresh": 1.0,
+      "window": 0.5,
+      "gain": 1.0,
+      "alpha": 0.9,
+      "readout": "spikecount",
+      "fake_quant": 0,
+      "amp": false,
+      "spike_reg": 0.0,
+      "event_eval": true,
+      "decision_margin": 2.0,
+      "export": false,
+      "seed": 1234,
+      "hub_dir": "/kaggle/working/hub/opt08_mint_quant/w_bits_2",
+      "repo_id": "UWU-R-13/SSVEP-SNN",
+      "push_hf": false,
+      "keep_epoch_weights": 1,
+      "no_resume": true,
+      "selftest": false,
+      "baseline": false,
+      "bench": true,
+      "bench_warmup": 10,
+      "bench_iters": 50,
+      "bench_train_steps": 20,
+      "w_bits": 2,
+      "u_bits": 2,
+      "leak_shift": 0,
+      "qat": true,
+      "bits_sweep": "2,4,8,0",
+      "l2_bytes": 2097152,
+      "sampling_rate": 250.0
+    }
+  },
+  "final_summary": {
+    "final_test_acc": 0.03214285714285714,
+    "final_test_target_acc": 0.03214285714285714,
+    "final_test_rest_recall": NaN,
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+    "best_epoch": 2,
+    "resplit": "block",
+    "class_weight": false,
+    "drop_rest": true,
+    "epochs": 60,
+    "method": "harmonic_matched",
+    "n_in": 2880,
+    "n_classes": 40,
+    "num_bins": 100
+  },
+  "event_driven_summary": {
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+    "num_ticks": 100,
+    "dt_ms": 50.0,
+    "margin_decision_acc": 0.03142857142857143,
+    "mean_decision_tick": 84.10142857142857,
+    "mean_decision_ms": 4205.071428571428,
+    "dense_forward_test_acc": 0.03214285714285714
+  },
+  "extra_sweep_file_present": true,
+  "selftest": {
+    "mode": "gate",
+    "passed": true
+  },
+  "driver_version": 1,
+  "zip": {
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+  }
+}

applied/opt08_mint_quant/w_bits_2.zip

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