This study investigates the performance of Julia and compares it with the C and Python programming languages in solving problems involving one-dimensional vectors, matrix operations, and two-dimensional equations. Through a series of experiments, Julia’s performance on different computers with different numbers of CPU cores is measured and compared. We evaluated Julia’s performance using numerical symbols for one-dimensional vector and matrix equations on a single switch, and then tested Julia’s MPI implementation using 2D thermal equations in a multi-core Compute environment. The results show that Julia offers the best performance, often compared to C and better than Python, especially on tasks that require a lot of computation, such as one-dimensional vector operations and matrix multiplication. Comparison of the performance of C and Julia is illustrated by the simultaneous use of parallelism on both sides; This demonstrates the Julia language’s ability to use parallelism. Julia’s performance in performing computational tasks demonstrates her aptitude for computational science and statistical analysis.