70 lines
2.2 KiB
YAML
70 lines
2.2 KiB
YAML
# config/param.yaml
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# --- 1. 环境与路径配置 ---
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env:
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# 可执行文件绝对路径
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vasp_std: "mpirun -np 1 /cluster/home/koko125/vasp/bin_gpu/vasp_std"
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gpumd: "/cluster/home/koko125/tool/GPUMD/src/gpumd"
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nep: "/cluster/home/koko125/tool/GPUMD/src/nep"
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# GPUMDKit 脚本库根目录
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gpumdkit_root: "/cluster/home/koko125/tool/GPUMDkit"
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# 【修改点】HPC 作业提交配置 (用于填充 submit.slurm 模板)
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# 这些变量会被自动替换到 .sh 脚本头部
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# slurm_config:
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# partition: "v100" # 队列分区名
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# account: "def-user" # 账户名 (如果有)
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# gpu_per_node: 1 # 每节点 GPU 数
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# ntasks_per_node: 32 # 每节点 CPU 核数
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# time_limit: "24:00:00" # 墙钟时间限制
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# --- 2. 流程控制 ---
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# 阶段代号定义 (对应 modules 下的 Python 文件)
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stages_def:
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p: "preheat" # 00.md/preheat
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m: "md" # 00.md/md
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s: "select" # 01.select
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d: "scf" # 02.scf
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t: "train" # 03.train
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pr: "predict" # 04.predict (新增：用于性质预测)
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o: "output" # 05.output (始终默认执行：整理报告)
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# 自定义流程调度
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# 注意：'o' (output) 不需要显式写在这里，代码逻辑会强制每轮最后执行它
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schedule:
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# 第1轮: 跑完训练，不做预测，看一眼结果
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1: ["p", "m", "s", "d", "t"]
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# 第2轮: 跑完训练，加入预测步骤 (计算电导/扩散等)
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2: ["p", "m", "s", "d", "t", "pr"]
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# 默认流程 (如果没有定义轮次)
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default_workflow: ["p", "m", "s", "d", "t", "pr"]
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# --- 3. 容错与通知 ---
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control:
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max_retries: 3 # 任务失败自动重启次数
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check_interval: 60 # 状态检查间隔 (秒)
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notification:
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enable_log: true
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log_file: "./logs/sys_runtime.log"
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enable_hook: true
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hook_script: "python ./hooks/send_alert.py"
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alert_events: ["fail", "finish"]
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# --- 4. 模块参数 ---
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params:
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preheat:
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temp: 300
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steps: 10000
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select:
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target_min: 60
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target_max: 120
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init_threshold: 0.01
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predict:
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# 预测阶段需要的参数，比如计算电导率的温度范围
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temperatures: [300, 400, 500]
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script_path: "scripts/calc_conductivity.py" # 具体的计算脚本 |