MCQs on Concurrency and Parallelism | Haskell
Haskell is a powerful functional programming language that supports concurrency and parallelism, enabling efficient execution of multiple tasks simultaneously. Concurrency allows multiple tasks to progress without necessarily executing simultaneously, while parallelism takes advantage of multiple processors or cores to perform tasks at the same time. Haskell provides various abstractions like forkIO, MVar, Chan, and STM (Software Transactional Memory) for managing concurrency and parallel computation, making it a popular choice for high-performance applications.
Topics Overview:
- Introduction to concurrency in Haskell
- Using
forkIO,MVar, andChanfor concurrency - STM (Software Transactional Memory)
- Basic parallel computation and lazy parallelism
MCQs on Concurrency and Parallelism in Haskell
1. Introduction to Concurrency in Haskell
- What is the primary concept of concurrency in Haskell?
- A) Executing tasks on separate threads
- B) Managing multiple tasks simultaneously without direct synchronization
- C) Running tasks sequentially
- D) Distributing tasks across multiple machines
- Which of the following describes Haskell’s approach to concurrency?
- A) Cooperative multitasking
- B) Preemptive multitasking
- C) Explicit multithreading only
- D) No concurrency support
- Which abstraction does Haskell provide to manage concurrency?
- A) Threads
- B) Channels
- C) Forking
- D) MVar
- What is the main benefit of concurrency in Haskell?
- A) Parallel execution of code on multiple processors
- B) Efficient management of multiple independent tasks
- C) Automatic memory management
- D) Reducing CPU usage
- In Haskell, concurrency is achieved by:
- A) Using non-blocking IO
- B) Using
forkIOto create new threads - C) Automatically splitting tasks across processors
- D) Using lazy evaluation
2. Using forkIO, MVar, and Chan for Concurrency
- What does the
forkIOfunction in Haskell do?- A) It creates a new thread that runs concurrently
- B) It handles software transactional memory
- C) It synchronizes multiple threads
- D) It performs parallel computation
- Which data structure is used in Haskell to safely share state between threads?
- A) IORef
- B) MVar
- C) Chan
- D) List
- The
MVarin Haskell is used for:- A) Storing values in a thread-safe way
- B) Passing messages between threads
- C) Defining parallel tasks
- D) Synchronizing IO operations
- What is the primary use of
Chanin Haskell?- A) Managing IO operations
- B) Passing messages between threads
- C) Defining parallel computation
- D) Ensuring lazy evaluation
- Which of the following is true about
MVarandChan?- A) Both are designed for memory management
- B)
MVaris used for synchronization, whileChanis for message passing - C)
MVaris for parallel computation, whileChanis for lazy evaluation - D)
MVarandChanare interchangeable in Haskell
3. STM (Software Transactional Memory)
- What does STM stand for in Haskell?
- A) Synchronous Transaction Management
- B) Software Transactional Memory
- C) Single-threaded Memory
- D) Systematic Task Management
- What is the primary goal of STM in Haskell?
- A) To simplify concurrent programming by making it easier to handle shared memory
- B) To ensure that all threads run in parallel
- C) To avoid using memory in concurrent tasks
- D) To support lazy evaluation in multi-core systems
- Which function in Haskell is used to begin a transaction in STM?
- A)
atomically - B)
forkSTM - C)
runSTM - D)
executeTransaction
- A)
- What is a key advantage of using STM in Haskell?
- A) It avoids deadlocks by using retry mechanisms
- B) It ensures maximum CPU utilization
- C) It improves sequential performance
- D) It limits memory usage in multi-core systems
- Which of the following is a key feature of STM in Haskell?
- A) Non-blocking synchronization
- B) Transactional isolation of state changes
- C) Automatic garbage collection
- D) Direct manipulation of hardware
4. Basic Parallel Computation and Lazy Parallelism
- What does parallelism mean in Haskell?
- A) Running multiple tasks on different processors at the same time
- B) Performing tasks in sequence but managing them efficiently
- C) Lazy evaluation of tasks
- D) Using a single processor to manage multiple threads
- Which function in Haskell can be used for parallel computations?
- A)
par - B)
forkIO - C)
split - D)
runTask
- A)
- What is lazy parallelism in Haskell?
- A) Delaying computations until their results are needed
- B) Automatically distributing tasks across multiple processors
- C) Using STM to manage parallel tasks
- D) Running computations in sequence for better performance
- How does Haskell achieve parallelism without explicit multi-threading?
- A) Using lazy evaluation and parallel combinators
- B) Manually splitting tasks into threads
- C) Relying on external libraries for parallelism
- D) Using STM for automatic parallel execution
- In Haskell, the
parfunction is used for:- A) Parallelizing computations in a lazy manner
- B) Running tasks sequentially
- C) Synchronizing multiple threads
- D) Managing shared state between threads
Answer Key:
| Qno | Answer (Option with Text) |
|---|---|
| 1 | B) Managing multiple tasks simultaneously without direct synchronization |
| 2 | A) Cooperative multitasking |
| 3 | D) MVar |
| 4 | B) Efficient management of multiple independent tasks |
| 5 | B) Using forkIO to create new threads |
| 6 | A) It creates a new thread that runs concurrently |
| 7 | B) MVar |
| 8 | A) Storing values in a thread-safe way |
| 9 | B) Passing messages between threads |
| 10 | B) MVar is used for synchronization, while Chan is for message passing |
| 11 | B) Software Transactional Memory |
| 12 | A) To simplify concurrent programming by making it easier to handle shared memory |
| 13 | A) atomically |
| 14 | A) It avoids deadlocks by using retry mechanisms |
| 15 | B) Transactional isolation of state changes |
| 16 | A) Running multiple tasks on different processors at the same time |
| 17 | A) par |
| 18 | A) Delaying computations until their results are needed |
| 19 | A) Using lazy evaluation and parallel combinators |
| 20 | A) Parallelizing computations in a lazy manner |