Introducing Parallel Processing

Traditionally, software packages are written for serial computation:

• Run on a single computer with a single CPU.
• A problem is broken into a discrete series of instructions.
• Instructions are executed one after another.
• Only one instruction executes at any moment.

Parallel processing enables simultaneous use of multiple computer resources to solve a computational problem:

• Run using multiple CPUs.
• A problem is broken into several parts that can be solved concurrently.
• Each part is further broken down into a series of instructions.
• Instructions from each part execute simultaneously on different CPUs.

Thanks to technologies available at reduced cost (multi-core computers, clusters, etc.), parallel processing can achieve distributed computing with a reasonable investment — making it possible to solve long-running, computationally intensive problems, especially when large numbers of independent simulation runs are required (e.g. Monte Carlo studies, design of experiments, batch parametric sweeps).