Fix second implementation, add benchmark script

* Third implementation is broken (WIP)

examples/python_naive_matmul/benchmark.py

@@ -0,0 +1,49 @@
+import time
+
+import kp
+import numpy as np
+from imp1_naive import MatMulOp as MatMulOp1
+from imp2_tiled import MatMulOp as MatMulOp2
+from imp3_better_tiling import MatMulOp as MatMulOp3
+
+
+def main():
+    experiment_count = 1000
+    tensor_size = 512
+    tensor_shape = [tensor_size, tensor_size]
+    mat_1 = np.triu(np.ones(tensor_shape))
+    mat_2 = np.triu(np.ones(tensor_shape))
+    mat_result = mat_1 @ mat_2
+    tensor_shape = [tensor_size, tensor_size]
+
+    print(f'{tensor_shape} input tensors:\n'
+          f'{mat_1}\n'
+          f'{mat_2}\n')
+    print(f'Output :\n{mat_result}')
+
+    mgr = kp.Manager()
+    tensor_in_1 = mgr.tensor(mat_1)
+    tensor_in_2 = mgr.tensor(mat_2)
+    tensor_out = mgr.tensor(np.zeros(tensor_shape))
+    for MatMulOp in [MatMulOp1, MatMulOp2, MatMulOp3]:
+        matmul_op = MatMulOp(mgr)
+        matmul_op(tensor_shape, tensor_in_1, tensor_in_2, tensor_out)
+
+        start_time = time.time()
+        for _ in range(experiment_count):
+            matmul_op(tensor_shape, tensor_in_1, tensor_in_2, tensor_out)
+        end_time = time.time()
+        experiment_time = end_time - start_time
+        op_count = tensor_shape[0] * tensor_shape[1] * (tensor_shape[1] - 1)
+
+        if (tensor_out.data().reshape(tensor_shape) == mat_result).all():
+            print(f'From {MatMulOp.__module__} : {experiment_count} matmul time : '
+                  f'{experiment_time * 1000:0.2f}ms => '
+                  f'{experiment_count / experiment_time:0.2f}op/s or '
+                  f'{experiment_count * op_count / (1e9 * experiment_time):0.2f}GFLOPS')
+        else:
+            print(f'Test failed => output tensor is wrong :\n{tensor_out.data().reshape(tensor_shape)}')
+
+
+if __name__ == '__main__':
+    main()