Beginner Topic 8 of 51 Operating Systems
Threads
Lightweight execution units sharing a process's memory.
How it works
A thread is the smallest unit of CPU scheduling inside a process. Threads of one process share the same address space, heap, code and open files, but each has its own stack, registers and program counter. Creating and switching between threads is cheaper than for processes, and sharing data is easy through memory, which also makes races possible. Threads may be scheduled by the kernel or managed in user space.
Step-by-step walkthrough
- One process can contain several threads.
- A second thread starts in the same process.
- Each thread has its own stack and registers.
- They share code, heap and open files.
- Sharing makes communication fast but needs synchronization.
Where it is used
Web servers handling many requests, GUIs keeping the interface responsive during work, parallel computation on multicore CPUs and background tasks use threads.
Common pitfall
Shared memory causes race conditions, deadlocks and hard-to-reproduce bugs. A crash in one thread kills the whole process. Creating too many threads wastes memory and scheduling time; use thread pools. Protect shared data with locks or use message passing, and avoid sharing mutable state when possible.
Where it fits in the course
Threads is topic 8 of 51 in Operating Systems, rated Beginner. It follows Process Control Block. The next topic is Context Switching.
Practice and explore
- Open the interactive lesson, with a mini quiz.
- Take the Operating Systems quiz.
How to study this topic
- Read the explanation above and restate the definition in your own words.
- Open the interactive lesson and answer its mini quiz.
- Read the common pitfall, then write a short example that avoids it.
- Check your understanding in the Operating Systems quiz, and revisit the topic if you miss a question.
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Related topics
- Process Control Block (Operating Systems)
- Context Switching (Operating Systems)
- Process States (Operating Systems)
- CPU Scheduling (Operating Systems)
- Threads in Practice (Concurrency & Parallelism)
- Green Threads (Concurrency & Parallelism)