Parallel Programming Quiz

What is parallel programming?

• Writing code to be executed sequentially

• Writing code that can run across multiple processors simultaneously

• Writing code to handle only one task at a time

• Writing code without using functions

Which of the following is an example of a parallel programming model?

• Single-core processing

• Message Passing Interface (MPI)

• Assembler programming

• Object-oriented programming

What is the main goal of parallel programming?

• Increase the memory capacity

• Decrease the code readability

• Improve computational performance by splitting tasks

• Ensure code only runs on a single thread

Which of the following is NOT a common issue in parallel programming?

• Load balancing

• Data dependency

• Deadlocks

• Compiler optimization

Which of the following is an example of a tool used for parallel programming?

• Microsoft Excel

• OpenMP

• Adobe Photoshop

• SQL Server

Which of the following is true about data parallelism?

• It divides data across multiple processors and performs the same task on each

• It divides tasks, each of which is executed independently

• It performs the same operation multiple times on a single processor

• It requires no communication between processors

What does "synchronization" mean in the context of parallel programming?

• Combining multiple tasks into one large task

• Ensuring multiple processes or threads share data without conflicts

• Executing threads independently with no communication

• Running only one task at a time

Which programming model relies on shared memory for communication between threads?

• Distributed computing

• Threaded parallelism

• Dataflow programming

• Cloud computing

In parallel programming, "granularity" refers to:

• The level of detail in the code

• The size of tasks into which a program is divided

• The precision of data structures used in the program

• The amount of memory available to the program

What is "task parallelism"?

• Distributing data across different threads to process the same task

• Performing multiple distinct tasks concurrently on different processors

• A form of parallel programming that avoids synchronization

• Writing code that only runs on one processor at a time