In order to dramatically speed up your computations, you can create a program that uses multiple CPU cores in parallel instead of a single CPU core. Depending on the type of the problem, the speed-up could scale linearly with the number of cores. For example, on a quad-core machine, your program could run four times faster. When running on clusters with hundreds or thousands of CPUs, the benefits provided by parallel computing can be substantial. Various techniques are available to implement parallel computing, such as OpenMP, Python multiprocessing, or MPI.
This webpage provides information and resources on parallel computing, offering professors insights into the benefits and techniques of utilizing parallel processing to enhance computational power and efficiency in academic research and teaching.