Mastodawn

Concurrency Concept: Say you have two threads trying to access the same bytes.
Instead of a lock, both threads can reserve a specific time interval, in which they are allowed to access the memory area. So the access timeline would look something like this (t1 and t2 being the timeframe's the respective threads can access it): t1 | t2 | t1 | t2 | ...

#programming #concurrency #parallel #parallelism

Aiono May 12

Shoutout to @nushell for providing no-hassle parallelisation. I had a simple script which formats my Latex files like this:
```
def main [] {
let files = ls latex/**/*.tex | get name;
$files | each { |file|
let abs_path = $file | path expand;
latexindent --silent $abs_path --output $abs_path;
} | ignore;
}
```
which takes ~2 minutes to go through all my files. I just changed the `each` to `par-each` and voila! It got under 20 seconds!

#scripting #parallelism

Jeffrey04 Apr 8

https://kitfucoda.medium.com/concurrency-vs-parallelism-achieving-scalability-with-processpoolexecutor-c366bfcc6207

Concurrency and parallelism are often confused in async programming discussions. Go's goroutines highlighted the difference: concurrency is doing many things at once, while parallelism is doing many things at the same time.

AsyncIO handles concurrency well for I/O, but CPU-bound tasks need parallelism. Python uses AsyncIO for concurrency, and ProcessPoolExecutor for parallelism, distributing work across CPU cores.

Process communication is harder than thread communication. AsyncIO's task cancellation differs from ProcessPoolExecutor's, requiring workarounds like event objects for reliable cancellation and shutdown.

Essentially, ProcessPoolExecutor enables parallelism for CPU-bound tasks, scaling them across multiple cores, while AsyncIO handles I/O concurrently.

#python #asyncio #concurrency #parallelism #multiprocessing #opentowork #getfedihired #fedihire #opentowork

Concurrency vs. Parallelism: Achieving Scalability with ProcessPoolExecutor

In our previous exploration, we dove deep into AsyncIO by writing a task scheduler. We discovered how IO-bound operations were scheduled to the event loop concurrently while building our task…

Medium

C++Now Apr 2

C++Now 2025 SESSION ANNOUNCEMENT: Parallel Range Algorithms - The Evolution of Parallelism in C++ by Ruslan Arutyunyan

https://schedule.cppnow.org/session/2025/parallel-range-algorithms/

#algorithms #cplusplus #cpp26 #parallelism

Parallel Range Algorithms – C++Now Schedule

Paul Houle Mar 20

🏃‍♀️ High-performance computing, with much less code

(... back in my business development days I was interested in "rules and schemes" that would separate what is to be done with how it should be done)

https://news.mit.edu/2025/high-performance-computing-with-much-less-code-0313

#computing #software #programming #languages #hpc #parallelism

High-performance computing, with much less code

The “Exo 2” language allows programmers to write “schedules” that explicitly control how the compiler generates code. This allows performance engineers to transform simple programs into complex programs that do the same thing as the specification, but faster.

MIT News | Massachusetts Institute of Technology