Parallel Computing and Distributed Computing
Sequential computing has been great, but computer scientists need every speed and storage advantage they can get. Clever computer scientists have found even more efficient ways to use computer hardware for certain types of problems.

parallel Computing
Parallel computing ​is the use of a computer that performs multiple instructions at the same time. The programs used for parallel computing must be designed so they can be broken down into smaller independent parts that each processor can work on.

Parallel computing uses multiple computing cores. A computing core​ is one processor in the CPU. Parallel computers will have many different processors in their CPUs instead of just one.

Speedup in Parallel Computing
The advantage of a parallel computing solution over a sequential computing solution can be measured in speedup. Speedup​ is the amount of time used to perform a task with sequential computation divided by the amount of time used to perform the same task with parallel computation.

For example, imagine that you run a program on a sequential computer and it takes 10 minutes to complete. Next, you run the same program on a parallel computer and it takes 5 minutes to complete. You would divide the 10 by the 5 and come up with a speedup of 2. This means your program is two times faster on a parallel computer.

Distributed Computing
Many computer problems are so complex that they take an extremely long time to run on one computer. Distributed computing​ is the use of multiple computers to solve a problem. Distributed computing is like parallel computing but with many different computers; parallel computing is the use of one computer with many different processors.

QUESTION:
A program takes 10 minutes to compute sequentially and has a speedup of 2 on a parallel computer, meaning it takes how many minutes. ??