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.gitattributes

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+*.msgpack filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+title: PLUS Lab GPUs
+emoji: ➕
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 5.13.1
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import datetime
+import gradio as gr
+import pandas as pd
+import plotly.express as px
+
+def split_multi_users(dfs):
+    df = dfs.copy()
+    df["usernames"] = df["username"].apply(lambda x: x.split(", "))
+    df["count"] = 1
+    new_df = []
+    for row in df.to_dict(orient="records"):
+        gpu_users_num = len(row["usernames"])
+        for username in row["usernames"]:
+            new_row = row.copy()
+            new_row["count"] = 1 / gpu_users_num
+            new_row["username"] = username
+            new_df.append(new_row)
+    df = pd.DataFrame(new_df)
+    return df
+
+def plot_now():
+    dfs = pd.read_csv("hf://spaces/pluslab/PLUS_Lab_GPUs/gpus.csv")
+    dfs = dfs.drop(columns=["Unnamed: 0"])
+    dfs = dfs.fillna("FREE")
+    dfs_plot = split_multi_users(dfs)
+    fig = px.bar(
+        dfs_plot, x="count", y="server", color="username",
+        title=f"Last Updated {min(dfs['timestamp'])}",
+        color_discrete_map={
+            "FREE": "black",
+        },
+        text=dfs_plot['username'].astype(str) + "<br>" + dfs_plot['device'].astype(str),
+    )
+    fig.update_layout(
+        yaxis={'categoryorder': 'array', 'categoryarray': dfs_plot["server"].unique()[::-1]},
+        barcornerradius=50,
+    )
+    fig.update_traces(textposition='inside', insidetextanchor='middle')
+    print(dfs_plot)
+    return fig, dfs
+
+def plot_history(sample=True, sampling_interval_minutes=180):
+    dfh = pd.read_pickle("hf://spaces/pluslab/PLUS_Lab_GPUs/history.pkl.gz", )
+    dfh = dfh.fillna("FREE")
+    dfh = split_multi_users(dfh)
+    dfh = dfh[["polling_timestamp", "username", "count"]]
+    dfh = dfh.groupby(["polling_timestamp", "username"]).sum()
+    dfh = dfh.reset_index()
+    dfh = dfh.sort_values(by=["polling_timestamp", "count"], ascending=False)
+    if sample:
+        unique_timestamps = dfh["polling_timestamp"].unique()
+        sampled_timestamps = [unique_timestamps[0]]
+        for i, t in enumerate(unique_timestamps[1:]):
+            diff = sampled_timestamps[-1] - t
+            if diff > datetime.timedelta(minutes=sampling_interval_minutes):
+                sampled_timestamps.append(t)
+        dfh = dfh[dfh["polling_timestamp"].isin(sampled_timestamps)]
+    fig = px.area(dfh, x="polling_timestamp", y="count", color='username', color_discrete_map={"FREE": "black",}, markers=True, line_shape='spline',)
+    return fig, dfh
+
+
+def plot_figs():
+    fig_now, dfn = plot_now()
+    try:
+        fig_history, dfh = plot_history()
+    except Exception as e:
+        print(e)
+        fig_history = None
+        dfh = None
+    return fig_now, dfn, fig_history
+
+demo = gr.Interface(
+    fn=plot_figs,
+    inputs = [
+
+    ],
+    outputs = [
+        gr.Plot(label="GPU Status", elem_classes="plotcss"),
+        gr.Dataframe(label="GPU Status Details"),
+        gr.Plot(label="History", elem_classes="plotcss"),
+    ],
+    live=True,
+    flagging_options=[],
+    css=".plotcss {max-width: 820px !important;}"
+)
+
+if __name__ == "__main__":
+    demo.launch(debug=False)
+

gpus.csv

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+,timestamp,server,name,device,utilization.gpu [%],utilization.memory [%],temperature.gpu,power.draw [W],username
+0,2025/06/25 05:32:45.940,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,0,99 %,57 %,62,367.02 W,xueqing.wu
+1,2025/06/25 05:32:45.959,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,1,99 %,53 %,63,374.97 W,xueqing.wu
+2,2025/06/25 05:32:45.973,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,2,99 %,52 %,52,373.61 W,xueqing.wu
+3,2025/06/25 05:32:45.989,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,3,98 %,59 %,53,387.15 W,xueqing.wu
+0,2025/06/25 05:32:47.148,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,0,99 %,93 %,63,291.88 W,ponienkung
+1,2025/06/25 05:32:47.159,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,1,99 %,51 %,72,306.29 W,junyizhang
+2,2025/06/25 05:32:47.166,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,2,0 %,0 %,61,77.14 W,junyizhang
+3,2025/06/25 05:32:47.174,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,3,0 %,0 %,58,76.64 W,junyizhang
+4,2025/06/25 05:32:47.181,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,4,92 %,44 %,72,282.15 W,fanyin20
+5,2025/06/25 05:32:47.188,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,5,92 %,42 %,72,329.60 W,fanyin20
+6,2025/06/25 05:32:47.194,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,6,99 %,51 %,73,315.57 W,junyizhang
+7,2025/06/25 05:32:47.200,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,7,0 %,0 %,43,64.30 W,xueqing.wu
+0,2025/06/25 05:32:48.343,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,0,0 %,0 %,48,72.64 W,
+1,2025/06/25 05:32:48.360,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,1,0 %,0 %,48,78.20 W,
+2,2025/06/25 05:32:48.375,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,2,77 %,56 %,64,368.90 W,haikang
+3,2025/06/25 05:32:48.389,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,3,77 %,57 %,60,356.04 W,haikang
+4,2025/06/25 05:32:48.404,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,4,75 %,56 %,61,353.75 W,haikang
+5,2025/06/25 05:32:48.420,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,5,40 %,14 %,53,214.77 W,ponienkung
+6,2025/06/25 05:32:48.434,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,6,39 %,13 %,56,229.54 W,ponienkung
+7,2025/06/25 05:32:48.449,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,7,0 %,0 %,47,75.22 W,
+0,2025/06/25 05:32:49.926,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,0,100 %,1 %,85,187.87 W,xueqing.wu
+1,2025/06/25 05:32:49.942,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,1,99 %,3 %,59,194.41 W,xueqing.wu
+2,2025/06/25 05:32:49.951,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,2,99 %,3 %,66,199.23 W,xueqing.wu
+3,2025/06/25 05:32:49.961,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,3,96 %,3 %,62,190.80 W,xueqing.wu
+4,2025/06/25 05:32:49.971,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,4,0 %,0 %,30,22.88 W,
+5,2025/06/25 05:32:49.979,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,5,0 %,0 %,29,28.40 W,
+6,2025/06/25 05:32:49.986,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,6,0 %,0 %,31,26.89 W,
+7,2025/06/25 05:32:49.992,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,7,0 %,0 %,30,21.56 W,
+0,2025/06/25 05:32:51.188,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,0,0 %,0 %,69,97.21 W,xueqing.wu
+1,2025/06/25 05:32:51.194,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,1,0 %,0 %,60,87.13 W,xueqing.wu
+2,2025/06/25 05:32:51.197,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,2,16 %,12 %,73,259.84 W,xueqing.wu
+3,2025/06/25 05:32:51.199,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,3,0 %,0 %,63,86.67 W,xueqing.wu
+4,2025/06/25 05:32:51.201,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,4,0 %,0 %,26,22.41 W,
+5,2025/06/25 05:32:51.205,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,5,0 %,0 %,25,19.62 W,
+6,2025/06/25 05:32:51.210,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,6,0 %,0 %,27,20.53 W,
+7,2025/06/25 05:32:51.214,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,7,0 %,0 %,27,26.57 W,haikang
+0,2025/06/25 05:32:52.698,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,0,0 %,0 %,28,26.73 W,
+1,2025/06/25 05:32:52.726,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,1,0 %,0 %,26,30.76 W,
+2,2025/06/25 05:32:52.754,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,2,92 %,94 %,68,264.96 W,hzhang19
+3,2025/06/25 05:32:52.782,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,3,100 %,95 %,63,256.09 W,hzhang19
+4,2025/06/25 05:32:52.816,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,4,100 %,75 %,71,292.37 W,xueqing.wu
+5,2025/06/25 05:32:52.836,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,5,78 %,54 %,61,290.91 W,xueqing.wu
+6,2025/06/25 05:32:52.871,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,6,74 %,42 %,71,291.68 W,xueqing.wu
+7,2025/06/25 05:32:52.890,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,7,86 %,62 %,66,291.55 W,xueqing.wu

requirements.txt

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+plotly==5.24.1
+pandas==2.2.3