TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15422 · Jan 19

#c_lang TaskExplorer is a powerful Windows task manager that gives you deep insight into what your applications are doing in real-time. It displays process information in easy-to-use panels showing threads, memory, network connections, and system resources without cluttering your screen. You benefit from advanced diagnostic tools like stack traces for finding performance problems, memory editing capabilities, and detailed monitoring of disk operations and network activity. The streamlined interface lets you navigate quickly using arrow keys while watching live updates, making it ideal for troubleshooting software issues, optimizing system performance, and detecting problems that standard Task Manager cannot reveal. https://github.com/DavidXanatos/TaskExplorer

Hashtags

Results

1 similar post found

Search: #parallelism

当前筛选 #parallelism清除筛选
djangoproject

@djangoproject · Post #118 · 08/08/2016, 11:44 AM

https://docs.python.org/3/library/multiprocessing.html multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows. The #multiprocessing module also introduces #APIs which do not have analogs in the #threading#module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data #parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool,