Answer: conduct an experiment in chemistry.
Explanation:
Answer:
The program to this question can be given as:
Program:
def swap_values(user_val1, user_val2): #define function
return (user_val2, user_val1) #return values
if __name__ == '__main__': #define constructor.
n1 = int(input('Enter first number :')) #input value form user
n2 = int(input('Enter second number :')) #input value form user
(n1,n2) = swap_values(n1,n2) #hold function values.
print(n1) #print values
print(n2) #print values
Output:
Enter first number :3
Enter second number :8
8
3
Explanation:
The explanation of the above python program can be given as:
- In the python program we define a function that is "swap_values". This function takes two integer values that is "user_val1 and user_val2" as a parameters and returns variable values that is "user_val2 and user_val1".
- Then we use a constructor in this we define two variable that is "n1 and n2" these variable are use to take user-input from the user and pass the value into the function.
- To hold the value of the function we use n1 and n2 variable and print these variable value.
Answer:
1) bob behnken and doug hurley
2)yes
3) august
The discipline of building hardware architectures, operating systems, and specialized algorithms for running a program on a cluster of processors is known as <u>parallel computing.</u>
<u></u>
<h3>What is Parallel Computing?</h3>
Parallel computing refers to the process of breaking down larger problems into smaller, independent, often similar parts that can be executed simultaneously by multiple processors communicating via shared memory, the results of which are combined upon completion as part of an overall algorithm. The primary goal of parallel computing is to increase available computation power for faster application processing and problem solving.
<h3>Types of parallel computing</h3>
There are generally four types of parallel computing, available from both proprietary and open source parallel computing vendors:
- Bit-level parallelism: increases processor word size, which reduces the quantity of instructions the processor must execute in order to perform an operation on variables greater than the length of the word.
- Instruction-level parallelism: the hardware approach works upon dynamic parallelism, in which the processor decides at run-time which instructions to execute in parallel; the software approach works upon static parallelism, in which the compiler decides which instructions to execute in parallel.
- Task parallelism: a form of parallelization of computer code across multiple processors that runs several different tasks at the same time on the same data.
- Superword-level parallelism: a vectorization technique that can exploit parallelism of inline code.
Learn more about parallel computing
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