A global interpreter lock (GIL) is a mechanism used in computer-language interpreters to synchronize the execution of threads so that only one native thread (per process) can execute at a time. An interpreter that uses GIL always allows exactly one thread to execute at a time, even if run on a multi-core processor. Some popular interpreters that have GIL are CPython and Ruby MRI.
A global interpreter lock (GIL) is a mutual-exclusion lock held by a programming language interpreter thread to avoid sharing code that is not thread-safe with other threads. In implementations with a GIL, there is always one GIL for each interpreter process.
Applications running on implementations with a GIL can be designed to use separate processes to achieve full parallelism, as each process has its own interpreter and in turn has its own GIL. Otherwise, the GIL can be a significant barrier to parallelism.
Reasons for employing a global interpreter lock include:
increased speed of single-threaded programs (no necessity to acquire or release locks on all data structures separately),
easy integration of C libraries that usually are not thread-safe,
ease of implementation (having a single GIL is much simpler to implement than a lock-free interpreter or one using fine-grained locks).
A way to get around a GIL is creating a separate interpreter per thread, which is too expensive with most languages.
Use of a global interpreter lock in a language effectively limits the amount of parallelism reachable through concurrency of a single interpreter process with multiple threads. If the process is almost purely made up of interpreted code and does not make calls outside of the interpreter which block for long periods of time (allowing the GIL to be released by that thread while they process), there is likely to be very little increase in speed when running the process on a multiprocessor machine. Due to signaling with a CPU-bound thread, it can cause a significant slowdown, even on single processors.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Jython is an implementation of the Python programming language designed to run on the Java platform. The implementation was formerly known as JPython until 1999. Jython programs can import and use any Java class. Except for some standard modules, Jython programs use Java classes instead of Python modules. Jython includes almost all of the modules in the standard Python programming language distribution, lacking only some of the modules implemented originally in C. For example, a user interface in Jython could be written with Swing, AWT or SWT.
In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. The implementation of threads and processes differs between operating systems. In Modern Operating Systems, Tanenbaum shows that many distinct models of process organization are possible. In many cases, a thread is a component of a process.
Students learn several implementation techniques for modern functional and object-oriented programming languages. They put some of them into practice by developing key parts of a compiler and run time
Understanding of the principles and applications of functional programming, the fundamental models of program
execution, application of fundamental methods of program composition, meta-programming thr
Related lectures (6)
As hardware evolves, so do the needs of applications. To increase the performance of an application,
there exist two well-known approaches. These are scaling up an application, using a larger multi-core
platform, or scaling out, by distributing work to mul ...
Simulations of electrical activity of networks of morphologically detailed neuron models allow for a better understanding of the brain. State-of-the-art simulations describe the dynamics of ionic currents and biochemical processes within branching topologi ...
A priori, locking seems easy: To protect shared data from concurrent accesses, it is sufficient to lock before accessing the data and unlock after. Nevertheless, making locking efficient requires fine-tuning (a) the granularity of locks and (b) the locking ...
Explores the significance of lock-free synchronization for achieving low latency in distributed systems and discusses practical solutions for unique identifier generation and messaging queues.
Explores efficiently implementing a new programming language in GraalVM using partial evaluation and memory access profiling.
Explores interpreters and virtual machines, discussing their advantages, types, and optimization techniques.