Multithreading vs Multiprocessing Quiz and Flashcards for Data Science

What is the purpose of the Global Interpreter Lock (GIL) in Python?

Which of the following is an example of Inter-process communication (IPC)?

What is a potential issue that can arise when multiple threads access shared memory without proper synchronization?

If a CPU-bound task needs to be parallelized across multiple cores, which approach should be used in Python?

Which of the following is a common technique used for synchronizing access to shared resources between threads?

What is the advantage of using multiprocessing over multithreading for CPU-bound tasks in Python?

What is a potential drawback of using multiprocessing compared to multithreading in Python?

What is the purpose of using a mutex (mutual exclusion) in multithreaded programming?

Which of the following is a potential issue that can arise when using shared memory for inter-process communication?

What is the purpose of using a semaphore in multithreaded programming?

CPU, Cores, and Threads

A CPU (Central Processing Unit) executes instructions as a thread, which is the highest-level instruction in a CPU execution cycle.
A CPU core can execute one thread at a time, but it can switch between threads quickly, making it seem like multiple threads are running simultaneously.
A thread's state is written to main memory and its instructions are removed from the pipeline when it's not running, allowing another thread to start.

Threading and Multithreading

Threading is changing the attention of a CPU core between multiple threads.
A CPU core needs to figure out when to run which thread, even if a thread has no urgent reason to be executed (e.g., waiting for user input or data to be loaded).

Multicore and Multiprocessing

Multiple cores allow multiple threads to run simultaneously, increasing processing speed.
The introduction of dual cores in CPUs in 2000 by IBM and later by Sun and HP in 2004 marked a significant milestone.
The first dual-core chips for x86-based PCs and servers were introduced in 2005 by Intel and AMD.

Hyperthreading (SMT)

Simultaneous multithreading (SMT) allows a CPU to create a virtual core for each physical core, optimizing instructions and increasing processing speed by 15-30%.
SMT requires only 5% more die surface, making it a more efficient solution.

Importance of Threads

Every Python program has at least one thread.
Threads are useful in GUIs to prevent the main thread from hanging when performing computations.
Threads are also useful for I/O bound problems and parallelizing data processing on shared data.

Communication between Threads

Synchronizing threads is necessary to prevent memory access race conditions.
PyQt Signal/Slots is a way to communicate between threads.

Learn about the differences between multithreading and multiprocessing and how they can help you parallelize your code in Data Science. Explore the concepts of CPU, cores, threads, clock rate, and instruction execution.