From cd99d6b874d9d09b3bb87b8485cc787885af71f1 Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Tue, 13 Jan 2026 23:49:05 -0600 Subject: init commit --- scripts/run_depth_scaling_cifar10.sbatch | 56 ++++++++++++++++++++++++++++++++ 1 file changed, 56 insertions(+) create mode 100644 scripts/run_depth_scaling_cifar10.sbatch (limited to 'scripts/run_depth_scaling_cifar10.sbatch') diff --git a/scripts/run_depth_scaling_cifar10.sbatch b/scripts/run_depth_scaling_cifar10.sbatch new file mode 100644 index 0000000..28fbf06 --- /dev/null +++ b/scripts/run_depth_scaling_cifar10.sbatch @@ -0,0 +1,56 @@ +#!/bin/bash +#SBATCH --job-name=snn_cifar10_depth +#SBATCH --account=bfqt-delta-gpu +#SBATCH --partition=gpuA40x4 +#SBATCH --nodes=1 +#SBATCH --ntasks=1 +#SBATCH --cpus-per-task=8 +#SBATCH --gpus-per-node=1 +#SBATCH --mem=32G +#SBATCH --time=48:00:00 +#SBATCH --output=runs/slurm_logs/%j_cifar10_depth.out +#SBATCH --error=runs/slurm_logs/%j_cifar10_depth.err + +# ============================================================ +# CIFAR-10 Depth Scaling Benchmark (Baseline) +# ============================================================ +# CIFAR-10 is easier (10 classes) - used as baseline comparison. +# +# Reference from literature: +# - Spiking VGG 7 layers: ~88% accuracy +# - Spiking VGG 13 layers: ~91.6% accuracy +# +# This experiment validates our implementation against known results. +# ============================================================ + +set -e + +PROJECT_DIR="/projects/bfqt/users/yurenh2/ml-projects/snn-training" +cd "$PROJECT_DIR" + +mkdir -p runs/slurm_logs data + +echo "============================================================" +echo "CIFAR-10 Depth Scaling Benchmark" +echo "Job ID: $SLURM_JOB_ID | Node: $SLURM_NODELIST" +echo "Start: $(date)" +echo "============================================================" +nvidia-smi --query-gpu=name,memory.total --format=csv,noheader +echo "============================================================" + +python files/experiments/depth_scaling_benchmark.py \ + --dataset cifar10 \ + --depths 4 8 12 16 \ + --T 4 \ + --epochs 100 \ + --batch_size 128 \ + --lr 0.001 \ + --lambda_reg 0.3 \ + --lambda_target -0.1 \ + --data_dir ./data \ + --out_dir runs/depth_scaling \ + --device cuda + +echo "============================================================" +echo "Finished: $(date)" +echo "============================================================" -- cgit v1.2.3