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.gitattributes

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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 08:13:49.661,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,0,0 %,0 %,30,52.88 W,
+1,2025/06/25 08:13:49.683,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,1,0 %,0 %,30,52.50 W,
+2,2025/06/25 08:13:49.702,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,2,0 %,0 %,27,52.34 W,
+3,2025/06/25 08:13:49.720,pluslab-a100.cs.ucla.edu,NVIDIA A100-SXM4-40GB,3,0 %,0 %,28,53.70 W,
+0,2025/06/25 08:13:50.852,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,0,99 %,96 %,66,309.69 W,ponienkung
+1,2025/06/25 08:13:50.865,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,1,23 %,5 %,50,97.39 W,aaron68lee
+2,2025/06/25 08:13:50.872,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,2,99 %,50 %,74,273.91 W,junyizhang
+3,2025/06/25 08:13:50.881,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,3,100 %,41 %,73,314.29 W,junyizhang
+4,2025/06/25 08:13:50.887,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,4,97 %,52 %,73,301.90 W,fanyin20
+5,2025/06/25 08:13:50.895,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,5,97 %,54 %,72,294.88 W,fanyin20
+6,2025/06/25 08:13:50.906,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,6,0 %,0 %,43,45.78 W,
+7,2025/06/25 08:13:50.914,pluslab01-a100.cs.ucla.edu,NVIDIA A100 80GB PCIe,7,0 %,0 %,43,64.74 W,xueqing.wu
+0,2025/06/25 08:13:52.069,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,0,0 %,0 %,53,74.28 W,
+1,2025/06/25 08:13:52.093,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,1,87 %,49 %,73,615.91 W,ponienkung
+2,2025/06/25 08:13:52.107,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,2,79 %,58 %,61,370.31 W,haikang
+3,2025/06/25 08:13:52.122,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,3,78 %,58 %,57,360.18 W,haikang
+4,2025/06/25 08:13:52.144,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,4,0 %,0 %,51,76.36 W,
+5,2025/06/25 08:13:52.159,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,5,86 %,50 %,72,628.88 W,ponienkung
+6,2025/06/25 08:13:52.173,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,6,87 %,50 %,78,646.38 W,ponienkung
+7,2025/06/25 08:13:52.188,pluslab01-h100.cs.ucla.edu,NVIDIA H100 80GB HBM3,7,88 %,49 %,71,606.92 W,ponienkung
+0,2025/06/25 08:13:53.838,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,0,0 %,0 %,56,19.86 W,xueqing.wu
+1,2025/06/25 08:13:53.848,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,1,0 %,0 %,51,24.38 W,xueqing.wu
+2,2025/06/25 08:13:53.858,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,2,0 %,0 %,57,25.47 W,xueqing.wu
+3,2025/06/25 08:13:53.872,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,3,0 %,0 %,52,16.61 W,xueqing.wu
+4,2025/06/25 08:13:53.881,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,4,0 %,0 %,32,22.18 W,
+5,2025/06/25 08:13:53.888,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,5,0 %,0 %,31,28.94 W,
+6,2025/06/25 08:13:53.895,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,6,0 %,0 %,33,27.56 W,
+7,2025/06/25 08:13:53.902,pluslab-a6000.cs.ucla.edu,NVIDIA RTX A6000,7,0 %,0 %,31,21.99 W,
+0,2025/06/25 08:13:55.118,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,0,100 %,69 %,71,296.75 W,xueqing.wu
+1,2025/06/25 08:13:55.125,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,1,100 %,66 %,65,292.56 W,xueqing.wu
+2,2025/06/25 08:13:55.128,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,2,100 %,68 %,69,294.61 W,xueqing.wu
+3,2025/06/25 08:13:55.130,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,3,100 %,65 %,65,294.64 W,xueqing.wu
+4,2025/06/25 08:13:55.134,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,4,0 %,0 %,29,22.40 W,
+5,2025/06/25 08:13:55.138,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,5,0 %,0 %,28,19.04 W,
+6,2025/06/25 08:13:55.142,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,6,0 %,0 %,29,20.71 W,
+7,2025/06/25 08:13:55.146,pluslab01-a6000.cs.ucla.edu,NVIDIA RTX A6000,7,0 %,0 %,28,26.61 W,haikang
+0,2025/06/25 08:13:56.644,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,0,0 %,0 %,30,26.54 W,
+1,2025/06/25 08:13:56.668,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,1,0 %,0 %,28,30.75 W,
+2,2025/06/25 08:13:56.689,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,2,94 %,100 %,69,267.33 W,hzhang19
+3,2025/06/25 08:13:56.704,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,3,100 %,45 %,63,270.13 W,hzhang19
+4,2025/06/25 08:13:56.722,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,4,100 %,58 %,75,282.12 W,xueqing.wu
+5,2025/06/25 08:13:56.742,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,5,100 %,60 %,65,280.07 W,xueqing.wu
+6,2025/06/25 08:13:56.762,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,6,100 %,61 %,75,281.76 W,xueqing.wu
+7,2025/06/25 08:13:56.778,pluslab02-a6000.cs.ucla.edu,NVIDIA RTX A6000,7,100 %,55 %,70,275.80 W,xueqing.wu

requirements.txt

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+plotly==5.24.1
+pandas==2.2.3