numpy performance reached on reasonable matrix size

benchmarks/py_dot.py

@@ -0,0 +1,22 @@
+import os
+os.environ['OMP_NUM_THREADS'] = '1'
+
+import numpy as np
+import time
+
+N = 1024
+
+if __name__ == "__main__":
+    A = np.random.randn(N,N).astype(np.float64)
+    B = np.random.randn(N,N).astype(np.float64)
+
+    start = time.monotonic()
+    C = A @ B
+    stop = time.monotonic()
+    
+    s = stop-start
+    
+    ops = 2*N*N*N
+    
+    print(f"NUMPY: {ops/s * 1e-9} GFLOPS\n")
+