4 Main Differences b/w Parallel Computing & Distributed Computing

Parallel Computing vs Distributed Computing

Parallel Computing:

Transfer of Data at the same time for more than one processor. Process large data with multiple processors at the same time to save time and provide concurrency.

Distributed Computing:

Solve a single large and complex problem by using multiple computers or a network of computers. The results of each task are then combined to produce a final solution.

Example:

Multi-Core Processor is the best example of Parallel Computing.

Browsing or searching on the internet is an example of Distributed Computing.

Difference b/w Parallel Computing & Distributed Computing

1. Scale:

In Parallel Computing, multiple processors is used with a single machine or device while in Distributed Computing, multiple devices are connected all over the network.

2. Resource Sharing:

Resources are shared within the single machine in Parallel Computing but in Distributed Computing it is shared all over the network.

3. Synchronization:

Due to the proximity of processors, synchronization is easier in Parallel Computing while its is complex because of network latency in Distributed Computing.

4. Failure Handling:

If one processor fails, the other will work accordingly in Parallel Computing but in Distributed Computing if one node fails it will disturb the whole network and the whole network will fail.

Note: The difference between both varies according to the condition.

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