diff --git a/code/threads_indep.py b/code/threads_indep.py
index 1a4fd1b2..08103025 100644
--- a/code/threads_indep.py
+++ b/code/threads_indep.py
@@ -1,5 +1,6 @@
 import gc
 import time
+import numpy as np
 from numba import njit, prange
 from time_measurement import time_measurement_longest, longest_threads_time_accumulator, tests_time
 import linear_algebra_utils as linAlg
@@ -8,23 +9,28 @@ import linear_algebra_utils as linAlg
 @njit(parallel=True)
 def numba_matrix_vector_multiply(A, input_x, Ax):
     for i in prange(len(A)):
-        Ax[i] = sum(A[i][j] * input_x[j] for j in range(len(input_x)))
+        acc = 0.0
+        for j in range(len(input_x)):
+            acc += A[i][j] * input_x[j]
+        Ax[i] = acc
 
 @njit(parallel=True)
 def numba_vector_vector_subtraction(b, Ax, residual):
     for i in prange(len(b)):
         residual[i] = b[i] - Ax[i]
 
-@njit(parallel=True)
+@njit(nopython=True)
 def numba_scalar_vector_multiply(omega, vector, result):
-    for i in prange(len(vector)):
-        result[i] = omega * vector[i]
+    omega_real = omega.real 
+    for i in range(len(vector)):
+        result[i] = omega_real * vector[i]
 
 @njit(parallel=True)
 def numba_vector_vector_addition(input_x, vector, output_x):
     for i in prange(len(input_x)):
         output_x[i] = input_x[i] + vector[i]
 
+
 # Funkcje z dekoratorem
 @time_measurement_longest(longest_threads_time_accumulator)
 def matrix_vector_multiply(A, input_x, Ax):