There are several factors that motivate the use of parallelism in computing:
1. Increasing demand for processing power: As technology advances and data sets grow larger and more complex, the need for processing power has increased significantly.
Parallel computing allows for faster processing times and the ability to handle larger and more complex problems than traditional computing methods.
2. Hardware advancements: Modern processors and computing systems are designed to support parallelism, with multiple cores or processors built into a single chip or machine.
This makes it easier and more cost-effective to implement parallel computing.
3. Improved performance: Parallel computing can improve the performance of applications by enabling them to execute multiple tasks simultaneously, rather than waiting for each task to be completed sequentially.
4. Cost-effectiveness: Parallel computing can be more cost-effective than traditional computing methods, as it allows for the use of multiple processors or computers to work together on a single task, rather than requiring a single, expensive high-performance computing system.
5. Real-time processing: Parallel computing can enable real-time processing of data, which is critical in applications such as video streaming, gaming, and financial trading.
Overall, the demand for faster and more efficient processing, combined with hardware advancements and cost-effectiveness, makes parallel computing an attractive option for many modern applications.