01 - Choice of Kernel: NumPy vs Numba#
Description#
Here we compare Numba JIT-compiled kernels vs pure NumPy implementations. This experiment tests only the computational kernel in isolation - without MPI, domain decomposition, or parallel communication.
Purpose#
Identify impacts of the choice of kernel implementations and parameters like thread-count.
Kernel correctness - Verify both implementations produce identical results
Performance pr. iteration - Compare execution time for NumPy vs Numba with different thread counts across various problem sizes
Speedup analysis - Comparing different Numba thread configurations against a NumPy baseline.
Compute time scaling - Measure computation cost with fixed iteration count and also fixed tolerance.
Decision Point: Choose optimal kernel (NumPy or Numba) and thread count for subsequent experiments.
