What's the difference between sequential and parallel algorithms?

Sequential algorithms execute one operation at a time, while parallel algorithms perform multiple operations simultaneously.

Sequential algorithms are a type of algorithm where each step is executed one after the other, in a specific order. This means that the next step can only begin once the previous one has been completed. This type of algorithm is typically used when the output of one step is required as the input for the next. Sequential algorithms are easier to design and implement, but they may not be as efficient as parallel algorithms, especially when dealing with large data sets or complex computations.

On the other hand, parallel algorithms divide the problem into multiple sub-problems and solve them concurrently. This is achieved by using multiple processing elements (like cores in a multi-core processor) to execute different parts of the algorithm at the same time. The results from these concurrent operations are then combined to produce the final output. Parallel algorithms are more complex to design and implement, as they require careful coordination and synchronisation to ensure that all the processing elements are working correctly together. However, they can significantly reduce the time required to solve a problem, making them ideal for tasks that need to process large amounts of data or perform complex computations quickly.

In summary, the main difference between sequential and parallel algorithms lies in how they execute operations. Sequential algorithms follow a step-by-step approach, executing one operation at a time, while parallel algorithms divide the problem into smaller parts and solve them concurrently. The choice between using a sequential or parallel algorithm depends on the nature of the problem, the resources available, and the performance requirements.