Parallel Processing Quiz 4

1. Barrier synchronizations should be used whenever we want to ensure all threads have completed a common phase of their execution_____________

Before any of them start the next phase

After any of them start the next phase

Before any of them start the previous phase

After any of them start the previous phase

Barrier synchronizations should be used whenever we want to ensure all threads have completed a common phase of their execution before any of them start the next phase. This ensures that all threads have finished their current phase before moving on to the next phase, preventing any potential race conditions or inconsistencies in the program's execution.

Explanation

Barrier synchronizations should be used whenever we want to ensure all threads have completed a common phase of their execution before any of them start the next phase. This ensures that all threads have finished their current phase before moving on to the next phase, preventing any potential race conditions or inconsistencies in the program's execution.

2. OpenMP follows fork/join model becau

OpenMP programs start with a single thread

It initiates with a single thread and further a team of threads is created

Statements in parallel block are executed in parallel by every thread

OpenMP follows the fork/join model because at the start of a parallel region, the master thread creates a team of parallel worker threads. These threads then execute the statements in the parallel block in parallel. At the end of the parallel region, all the threads synchronize and join the master thread. This model allows for efficient parallel execution of code by dividing the work among multiple threads and then joining them back together.

Explanation

OpenMP follows the fork/join model because at the start of a parallel region, the master thread creates a team of parallel worker threads. These threads then execute the statements in the parallel block in parallel. At the end of the parallel region, all the threads synchronize and join the master thread. This model allows for efficient parallel execution of code by dividing the work among multiple threads and then joining them back together.

3.

Consider the following piece of code:

#include <omp.h>#include <stdio.h> int main(void){ #pragma omp parallel for{for (i=0; i<100; i++)printf ("Parallel Processing Quiz.\n");}return 0;} How many times "Parallel Processing Quiz" will get printed?

100 times

1000 times

10 times

Can't Predict

The code snippet is using OpenMP parallel for directive to parallelize the for loop. The loop will be divided among the available threads, and each thread will execute a portion of the loop. Since there is no dependency or synchronization involved, each thread will independently print "Parallel Processing Quiz" 100 times. Therefore, the total number of times "Parallel Processing Quiz" will get printed is 100.

Explanation

The code snippet is using OpenMP parallel for directive to parallelize the for loop. The loop will be divided among the available threads, and each thread will execute a portion of the loop. Since there is no dependency or synchronization involved, each thread will independently print "Parallel Processing Quiz" 100 times. Therefore, the total number of times "Parallel Processing Quiz" will get printed is 100.

4. omp_get_thread_num () environment variable gives:

Maximum number of threads in a team

Thread ID of the thread

Both a) and b)

None

The omp_get_thread_num() environment variable returns the Thread ID of the thread. This means that it provides a unique identifier for each thread in a parallel region. It does not give the maximum number of threads in a team, as that information can be obtained using omp_get_num_threads() function. Therefore, the correct answer is "Thread ID of the thread".

Explanation

The omp_get_thread_num() environment variable returns the Thread ID of the thread. This means that it provides a unique identifier for each thread in a parallel region. It does not give the maximum number of threads in a team, as that information can be obtained using omp_get_num_threads() function. Therefore, the correct answer is "Thread ID of the thread".

5.

Is the following piece of code correct?

int main(void){ L1: printf ("\n This is valid\n");#pragma omp parallel forfor (i=0; i<100; i++){printf ("Parallel Processing Quiz.\n");if (i==i%10)goto L1;}return 0;}

True

False

The given piece of code is incorrect because it contains a label "L1" which is being used with a goto statement inside the parallel for loop. The presence of the goto statement can lead to unpredictable behavior and can cause the program to jump to a different part of the code, which can result in errors or unexpected output.

Explanation

The given piece of code is incorrect because it contains a label "L1" which is being used with a goto statement inside the parallel for loop. The presence of the goto statement can lead to unpredictable behavior and can cause the program to jump to a different part of the code, which can result in errors or unexpected output.

6. If both export OMP_NUM_THREADS and omp_set_num_threads both are used in a program than the threads will be set to launch the parallel section in accordance with-

Omp_set_num_threads

OMP_NUM_THREADS

Whichever sets maximum number of threads

Whichever sets minimum number of threads

If both export OMP_NUM_THREADS and omp_set_num_threads are used in a program, the threads will be set to launch the parallel section in accordance with omp_set_num_threads. This is because omp_set_num_threads specifically sets the number of threads to be used in the parallel section, while export OMP_NUM_THREADS is a global environment variable that sets the maximum number of threads that can be used. Therefore, omp_set_num_threads takes precedence over OMP_NUM_THREADS in determining the number of threads to be used in the program.

Explanation

If both export OMP_NUM_THREADS and omp_set_num_threads are used in a program, the threads will be set to launch the parallel section in accordance with omp_set_num_threads. This is because omp_set_num_threads specifically sets the number of threads to be used in the parallel section, while export OMP_NUM_THREADS is a global environment variable that sets the maximum number of threads that can be used. Therefore, omp_set_num_threads takes precedence over OMP_NUM_THREADS in determining the number of threads to be used in the program.

7. omp_get_num_threads () environment variable gives:

Thread ID of all the threads

Maximum number of threads in a team

Return number of threads in a team

None

The omp_get_num_threads() environment variable returns the number of threads in a team. This means that it provides information about the total number of threads that are currently active and working together as a team. It does not give the thread ID of all the threads or the maximum number of threads in a team.

Explanation

The omp_get_num_threads() environment variable returns the number of threads in a team. This means that it provides information about the total number of threads that are currently active and working together as a team. It does not give the thread ID of all the threads or the maximum number of threads in a team.

8. OpenMP is:

A standard for Distributed Programming Model

A standard for uniprocessor optimization

A standard for writing parallel applications that supports shared programming model

All of the above

OpenMP is a standard for writing parallel applications that supports a shared programming model. This means that OpenMP allows multiple threads to work together on a single task, sharing data and resources. It provides a set of directives and libraries that enable developers to parallelize their code and take advantage of multi-core processors. OpenMP is not specifically designed for distributed programming or uniprocessor optimization, although it can be used in those contexts as well. Therefore, the correct answer is "A standard for writing parallel applications that supports shared programming model."

Explanation

OpenMP is a standard for writing parallel applications that supports a shared programming model. This means that OpenMP allows multiple threads to work together on a single task, sharing data and resources. It provides a set of directives and libraries that enable developers to parallelize their code and take advantage of multi-core processors. OpenMP is not specifically designed for distributed programming or uniprocessor optimization, although it can be used in those contexts as well. Therefore, the correct answer is "A standard for writing parallel applications that supports shared programming model."

9.

Consider the following piece of code:

#include #include int main(void){omp_set_num_threads (10);#pragma omp parallel {for (i=0; i<100; i++)printf ("Parallel Processing Quiz.\n");}return 0;} How many times "Parallel Processing Quiz" will get printed?

100 times

1000 times

10 times

Can't predict

The code snippet sets the number of threads to 10 using the omp_set_num_threads function. Then, it enters a parallel region using the #pragma omp parallel directive. Within this parallel region, each thread will execute the for loop that iterates 100 times and prints "Parallel Processing Quiz" each time. Since there are 10 threads, each thread will execute the for loop 100 times, resulting in a total of 1000 times that "Parallel Processing Quiz" will be printed.

Explanation

The code snippet sets the number of threads to 10 using the omp_set_num_threads function. Then, it enters a parallel region using the #pragma omp parallel directive. Within this parallel region, each thread will execute the for loop that iterates 100 times and prints "Parallel Processing Quiz" each time. Since there are 10 threads, each thread will execute the for loop 100 times, resulting in a total of 1000 times that "Parallel Processing Quiz" will be printed.

10. Consider the following piece of code:#include <omp.h>#include <stdio.h> int main(void){#pragma omp parallel{for (i=0; i<100; i++)printf ("Parallel Processing Quiz.\n");}return 0;} How many times "Parallel Processing Quiz" will get printed?

100 times

1 time

400 times

Can't predict

The code includes a parallel region defined by the pragma omp parallel directive. This means that the code inside the parallel region will be executed by multiple threads in parallel. Inside the parallel region, there is a for loop that iterates 100 times and prints "Parallel Processing Quiz" each time. Since the for loop is executed by multiple threads in parallel, the statement will be printed 100 times.

Explanation

The code includes a parallel region defined by the pragma omp parallel directive. This means that the code inside the parallel region will be executed by multiple threads in parallel. Inside the parallel region, there is a for loop that iterates 100 times and prints "Parallel Processing Quiz" each time. Since the for loop is executed by multiple threads in parallel, the statement will be printed 100 times.