tools: intel_gpu_analyser

This tool is intended to analyse statistics collected by intel_gpu_top and
kperf, and output summarized results for:
 - CPU usage (user and system time)
 - GPU usage (overall and per-ring)
 - Power usage in watts over time
 - Power usage relationship to CPU
 - Power usage relationship to GPU
 - Execution statistics

For perf outputs, the entire recorded perf execution is processed in
converted into a series of 'perf top'-like outputs for each process, for
each second of the execution.

Signed-off-by: Eugeni Dodonov <eugeni.dodonov@intel.com>

1 files changed, 55 insertions, 0 deletions

diff --git a/tools/intel_gpu_analyser.py b/tools/intel_gpu_analyser.py
new file mode 100755
index 0000000..a5b92f1
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+++ b/tools/intel_gpu_analyser.py
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+#!/usr/bin/python
+#
+# Intel GPU Top data analyser
+#
+
+import sys
+import os
+
+def collect(command):
+    """Collects statistics for a given command"""
+    print "Running %s" % command
+    fd = os.popen("intel_gpu_top -o - -e \"%s\"" % command)
+    results = {'time': [],
+            'utime': [],
+            'stime': [],
+            'power': [],
+            'render': [],
+            'bitstr': [],
+            'bitstr2': [],
+            'blitter': []
+            }
+    while True:
+        line = fd.readline()
+        if not line:
+            break
+        line.strip()
+        if line[0] == "#":
+            continue
+        data = line.split()
+        results['time'].append(float(data[0]))
+        results['utime'].append(float(data[1]))
+        results['stime'].append(float(data[2]))
+        results['power'].append(float(data[3]))
+        results['render'].append(float(data[4]))
+        results['bitstr'].append(float(data[6]))
+        results['bitstr2'].append(float(data[8]))
+        results['blitter'].append(float(data[10]))
+    return results
+
+def analyse(results):
+    """Analyses intel_gpu_top results"""
+    minpower = min(results['power'])
+    maxpower = max(results['power'])
+    avgpower = sum(results['power']) / len(results['power'])
+    print "Power: min %f, max %f, avg %f" % (minpower, maxpower, avgpower)
+    for iter in results:
+        pass
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        print "Usage: %s <command to profile>" % sys.argv[0]
+        sys.exit(1)
+    results = collect(sys.argv[1])
+    analyse(results)
+    print results