Let's now compare Numba to NumPy, ROCm, and CUDA in terms of simplicity in parallelization. In the following table, we explore the scope of Numba with respect to NumPy, ROCm, and CUDA to understand the scenarios when Numba could be advantageous to both. Some of the differences are as follows:
|
CUDA |
ROCm |
NumPy |
Numba |
|
Based on C/C++ programming language. |
Based on C/C++ programming language. |
Based on Python programming language. |
Based on Python programming language. |
|
Uses C/C++ combined with specialized code to accelerate computations. |
Uses C/C++ combined with specialized code to accelerate computations for HCC and HIP. |
Fundamental package for scientific computing with Python on conventional CPUs. |
Natively understands NumPy arrays, shapes, and dtypes and can index a NumPy array without relying on Python (close... |
