1 files changed, 74 insertions, 0 deletions
diff --git a/Common/nvidia.py b/Common/nvidia.py
new file mode 100644
index 0000000..88463b3
--- /dev/null
+++ b/Common/nvidia.py
@@ -0,0 +1,74 @@
+"""
+NVIDIA Interaction.
+"""
+
+import pandas as pd
+import numpy as np
+import glob as glob
+
+
+def read_gpu_stats(node='vesta1'):
+    """
+    Reads stats from CSV file, which was dumped on the GPU nodes.
+    
+    This query generates the CSV file. Run on GPU node.
+    nvidia-smi --query-gpu=index,uuid,name,temperature.gpu,utilization.gpu,utilization.memory,power.draw --format=csv,noheader > vesta1_`date '+%s'`.csv
+
+    CSV files is named "$node_$unix_epoch_in_seconds.csv".
+    For example, "vesta1_1454748497.csv".
+
+    @param: node - GPU node, used to nconstruct filename [String]
+    @return: df - GPU Stats [Pandas Dataframe]
+    @return: epoch - Time (Seconds since 01-01-1970) [Integer]
+    @return: success - Did we get data? [Boolean]
+    """
+
+    # Dev
+    # basedir = 'Test/'
+
+    # Prod
+    basedir = '/home/ics/volker/TmpDash/'
+
+    # Globbing
+    globs = glob.glob("%s/%s_*.csv" % (basedir, node))
+    globs = sorted(globs)
+    
+    # Is there anybody out there?
+    if len(globs) > 0:
+
+        # Extract Filename
+        fname = globs[-1]
+
+        # Extract Epoch
+        epoch = int(fname[:-4].split('_')[-1])
+
+        names_cols = [ 'gpu_id', 'uuid', 'gpu_name', 'gpu_temperature', \
+                       'gpu_utilization', 'memory_utilization', 'power_draw' ]
+        df = pd.read_csv(fname, sep=', ', header=None, names=names_cols, \
+                         engine='python')
+
+        # Drop Units
+        df.power_draw = \
+            df.power_draw.apply(lambda a: a.split(' ')[0])
+        df.gpu_utilization = \
+            df.gpu_utilization.apply(lambda a: a.split(' ')[0])
+        df.memory_utilization = \
+            df.memory_utilization.apply(lambda a: a.split(' ')[0])
+        
+        # Fix Types
+        df.power_draw = \
+            np.asarray(df.power_draw, dtype=np.float64)
+        df.gpu_utilization = \
+            np.asarray(df.gpu_utilization, dtype=np.float64)
+        df.memory_utilization = \
+            np.asarray(df.memory_utilization, dtype=np.float64)
+
+        # Add Node Column
+        df['node'] = pd.Series(["%s" % node]*len(df))
+
+        # Return
+        return df, epoch, True
+
+    else:
+        # Return
+        return None, None, False