background
background
background
background
background
background
background
Knowledge Base
backendadvanced

Concurrency and Parallelism: Threads, Locks, and Deadlocks

Concurrency and parallelism are critical concepts in software development, especially when building high-performance applications. Understanding threads, locks, and deadlocks can make or break your technical interview, as they are fundamental to efficiently managing tasks and ensuring robust system design. Before diving into concurrency and parallelism, ensure you're comfortable with:
3 min read1 views0 helpful
concurrencyparallelismthreadslocksdeadlocks
LinkedInTwitter / XWhatsApp

Learn this with Vidya

Have an AI tutor explain this concept to you through voice conversation

Start Session

Concurrency and parallelism are critical concepts in software development, especially when building high-performance applications. Understanding threads, locks, and deadlocks can make or break your technical interview, as they are fundamental to efficiently managing tasks and ensuring robust system design.

Prerequisites

Before diving into concurrency and parallelism, ensure you're comfortable with:

  • Basic programming concepts and data structures
  • Understanding of processes vs. threads
  • Familiarity with multithreading in any programming language
  • Basic knowledge of synchronization techniques

Understanding Concurrency vs. Parallelism

Concurrency and parallelism are often used interchangeably, but they describe different scenarios:

  • Concurrency refers to the ability of the system to handle multiple tasks at once, potentially overlapping in execution.
  • Parallelism involves executing multiple tasks simultaneously, often across multiple cores or processors.
graph TD;
    A[Start Task] --> B[Concurrency: Overlapping Execution]
    A --> C[Parallelism: Simultaneous Execution]

Threads

Threads are the smallest unit of processing that can be scheduled. They exist within processes and share memory space, making communication between them more efficient but also leading to potential conflicts.

Creating Threads

Here's a simple example of creating threads in Python:

import threading

def print_numbers():
    for i in range(5):
        print(i)

# Create and start a thread
thread = threading.Thread(target=print_numbers)
thread.start()
thread.join()

Sign up to read the full article

Get unlimited access to all knowledge base articles

Sign Up Free

Already have an account? Log in

Was this article helpful?

Related Articles

REST API Design: Best Practices and Common MistakesbeginnerSQL vs NoSQL: Choosing the Right DatabasebeginnerAuthentication and Authorization: OAuth, JWT, and SessionsintermediateDatabase Indexing: How Indexes Work Under the HoodintermediateGraphQL vs REST: When to Use Whatintermediate
#backend#concurrency#parallelism#threads#locks#deadlocks#mutex#interview-prep

Comments

Sign in to leave a comment