Add vector_add_observers_pmt example

Author: csbnw

examples/cuda/vector_add_observers_pmt.py

@@ -0,0 +1,49 @@
+#!/usr/bin/env python
+"""This is the minimal example from the README"""
+
+import json
+from collections import OrderedDict
+
+import numpy
+from kernel_tuner import tune_kernel
+from kernel_tuner.observers.pmt import PMTObserver
+
+def tune():
+
+    kernel_string = """
+    __global__ void vector_add(float *c, float *a, float *b, int n) {
+        int i = blockIdx.x * block_size_x + threadIdx.x;
+        if (i<n) {
+            c[i] = a[i] + b[i];
+        }
+    }
+    """
+
+    size = 80000000
+
+    a = numpy.random.randn(size).astype(numpy.float32)
+    b = numpy.random.randn(size).astype(numpy.float32)
+    c = numpy.zeros_like(b)
+    n = numpy.int32(size)
+
+    args = [c, a, b, n]
+
+    tune_params = dict()
+    tune_params["block_size_x"] = [128+64*i for i in range(15)]
+
+    pmtobserver = PMTObserver(["nvml", "rapl"])
+
+    metrics = OrderedDict()
+    metrics["GPU W"] = lambda p: p["nvml_power"]
+    metrics["CPU W"] = lambda p: p["rapl_power"]
+
+    results, env = tune_kernel("vector_add", kernel_string, size, args, tune_params, observers=[pmtobserver], metrics=metrics, iterations=32)
+
+    with open("vector_add.json", 'w') as fp:
+        json.dump(results, fp)
+
+    return results
+
+
+if __name__ == "__main__":
+    tune()