Why the Global Interpreter Lock?

by

In general, for any thread safety problem you will need to protect your internal data structures with locks.
This can be done with various levels of granularity.

  • You can use fine-grained locking, where every separate structure has its own lock.

  • You can use coarse-grained locking where one lock protects everything (the GIL approach).

There are various pros and cons of each method. Fine-grained locking allows greater parallelism – two threads can
execute in parallel when they don’t share any resources. However there is a much larger administrative overhead. For
every line of code, you may need to acquire and release several locks.

The coarse grained approach is the opposite. Two threads can’t run at the same time, but an individual thread will run faster because its not doing so much bookkeeping. Ultimately it comes down to a tradeoff between single-threaded speed and parallelism.

There have been a few attempts to remove the GIL in python, but the extra overhead for single threaded machines was generally too large. Some cases can actually be slower even on multi-processor machines
due to lock contention.

Do other languages that are compiled to bytecode employ a similar mechanism?

It varies, and it probably shouldn’t be considered a language property so much as an implementation property.
For instance, there are Python implementations such as Jython and IronPython which use the threading approach of their underlying VM, rather than a GIL approach. Additionally, the next version of Ruby looks to be moving towards introducing a GIL.

More Related Contents:

  1. Are locks unnecessary in multi-threaded Python code because of the GIL?
  2. Timeout on a function call
  3. Tkinter: How to use threads to preventing main event loop from “freezing”
  4. Can’t pickle when using multiprocessing Pool.map()
  5. Run certain code every n seconds [duplicate]
  6. What are the differences between the threading and multiprocessing modules?
  7. Creating Threads in python
  8. PyQt4 Wait in thread for user input from GUI
  9. How to terminate a thread when main program ends?
  10. How to make built-in containers (sets, dicts, lists) thread safe?
  11. Multithreaded web server in python
  12. How to run multiple jobs in one Sparkcontext from separate threads in PySpark?
  13. What is “thread local storage” in Python, and why do I need it?
  14. Python multithreaded print statements delayed until all threads complete execution
  15. why isn’t numpy.mean multithreaded?
  16. How to get the return value from a thread?
  17. Checking if a website is up via Python
  18. Are Generators Threadsafe?
  19. Is Keras thread safe?
  20. Python Tkinter Label redrawing every 10 seconds
  21. Using multiprocessing.Process with a maximum number of simultaneous processes
  22. Understanding Multiprocessing: Shared Memory Management, Locks and Queues in Python
  23. Threading in python using queue
  24. Execute Python function in Main thread from call in Dummy thread
  25. How do I create a file in python without overwriting an existing file
  26. How to implement a Lock with a timeout in Python 2.7
  27. Why does Paramiko hang if you use it while loading a module?
  28. Python: Why is threaded function slower than non thread
  29. Trigger an event when clipboard content changes
  30. Why doesn’t a string in parentheses make a tuple with just that string? [duplicate]

Leave a Comment