diff --git a/tests/kernel/tensor/check_correctness.py b/tests/kernel/tensor/check_correctness.py
index 94f25b2b..aa6147ce 100644
--- a/tests/kernel/tensor/check_correctness.py
+++ b/tests/kernel/tensor/check_correctness.py
@@ -41,9 +41,13 @@ def C_index(threadgroup, thread, register):
 def check_sim_output():
     file = input("simulator output filename: ")
 
-    A_array = np.zeros((16, 8))
-    B_array = np.zeros((8, 16))
-    C_array = np.zeros((16, 16))
+    M = 8
+    N = 8
+    K = 16
+
+    A_array = np.zeros((M, K))
+    B_array = np.zeros((K, N))
+    C_array = np.zeros((M, N))
 
     with open(file) as f:
         for line in f.readlines():
@@ -87,26 +91,23 @@ def check_sim_output():
 
 if __name__ == "__main__":
     expected = np.load("abc.npz")
-    # expected_A = expected['A_array']
-    # expected_B = expected['B_array']
-    # expected_C = expected['C_array']
-    expected_A = expected['A_array'][0:8, 0:8]
-    expected_B = expected['B_array'][0:8, 0:8]
-    expected_C = expected['C_array'][0:8, 0:8]
+    expected_A = expected['A_array']
+    expected_B = expected['B_array']
+    expected_C = expected['C_array']
     expected_C = expected_C + expected_A @ expected_B
     print('expected A:')
     print(expected_A)
     print('expected B:')
     print(expected_B)
     print('expected C:')
-    print(expected_C[0:8, 0:8])
+    print(expected_C)
     expected_C.astype('float32').tofile("c_expected.bin")
 
     [got_A, got_B, got_C] = check_sim_output()
     print('got C:')
-    print(C_array[0:8, 0:8])
+    print(C_array)
     print('diff C:')
-    print(expected_C[0:8, 0:8] - C_array[0:8, 0:8])
+    print(expected_C - C_array)
     assert np.allclose(expected_A, got_A)
     assert np.allclose(expected_B, got_B)
     assert np.allclose(expected_C, got_C)
diff --git a/tests/kernel/tensor/generate_matrix.py b/tests/kernel/tensor/generate_matrix.py
index 6833d58a..c549b4e9 100644
--- a/tests/kernel/tensor/generate_matrix.py
+++ b/tests/kernel/tensor/generate_matrix.py
@@ -1,10 +1,14 @@
 import numpy as np
 
+M = 8
+N = 8
+K = 16
+
 # A_array = np.random.rand(8, 16)
-A_array = np.arange(8 * 8).reshape([8, 8])
-B_array = np.arange(8 * 8).reshape([8, 8])
+A_array = np.arange(M * K).reshape([M, K])
+B_array = np.arange(K * N).reshape([K, N])
 # C_array = np.random.rand(16, 16)
-C_array = np.zeros([8, 8])
+C_array = np.zeros([M, N])
 # A_array = np.zeros((16, 8))
 # B_array = np.zeros((8, 16))
 # A_array[0,:] = 1.0
@@ -56,10 +60,10 @@ if __name__ == "__main__":
 
     np.savez("abc", A_array=A_array, B_array=B_array, C_array=C_array)
 
-    A_array.astype('float32').tofile("input.a.bin")
-    B_array.astype('float32').tofile("input.b.bin")
+    # A_array.astype('float32').tofile("input.a.bin")
+    # B_array.astype('float32').tofile("input.b.bin")
 
-    # A_array.astype('float16').tofile("input.a.bin")
-    # B_array = pack_fp16_by_column(B_array)
-    # B_array.astype('float16').tofile("input.b.bin")
+    A_array.astype('float16').tofile("input.a.bin")
+    B_array = pack_fp16_by_column(B_array)
+    B_array.astype('float16').tofile("input.b.bin")
     print(B_array)