@jesuisatire @mina @svenja @geist @GNUmatic

aloha monsieur JesuisSatire ,
ich lese ja schon gelegentlich mal drüber .. bin aber momentan an zu vielen projekten gleichzeitig dran , .. #ParallelComputing
performing #InfiniteRegression
https://quanticmusic.bandcamp.com/track/infinite-regression

btw. track 2 is my fav
// *-)

Infinite Regression, by Quantic

from the album The 5th Exotic

Quantic

We had a very productive F2F meeting last week at the Argonne Leadership Computing Facility, with many thanks to our great hosts at the Argonne National Lab. The main objective was to feature-freeze OpenMP API version 6.1 and we accomplished that mission!

#OpenMP #ParallelComputing #HPC

Sharing big R objects across processes shouldn’t mean copying them over and over.

mori uses shared memory + ALTREP to give you zero-copy access—multiple processes, one underlying object.

Fast, memory-efficient, and built for modern parallel workflows.

👉 https://shikokuchuo.net/mori/

#rstats #datascience #parallelcomputing

Shared Memory for R Objects

Share R objects across processes on the same machine via a single copy in POSIX shared memory (Linux, macOS) or a Win32 file mapping (Windows). Every process reads from the same physical pages through the R Alternative Representation (ALTREP) framework, giving lazy, zero-copy access. Shared objects serialize compactly as their shared memory name rather than their full contents.

The OpenMP Architecture Review Board has formed a #Python Language Subcommittee — a significant step toward bringing standardized shared-memory parallelism to the world's most widely used programming language.

The subcommittee's goal is to define #OpenMP directive support for Python and include it in the OpenMP API 7.0 specification, targeted for 2029.

https://www.openmp.org/2026/python-subcomittee/
#HPC #parallelcomputing

Python Language Subcommittee - OpenMP

The OpenMP ARB has formed a Python Language Subcommittee, to bringing the most used parallel programming API to the most popular programming language.

OpenMP
🎉 Wow, #groundbreaking revelation: when you give a hungry #AI agent a buffet of GPUs, it eats faster! 🚀 Who knew? Apparently, parallel computing is a thing now. 🙄 Thanks for the 12-minute read on how technology works, we were all clueless. 😂
https://blog.skypilot.co/scaling-autoresearch/ #parallelcomputing #technews #GPUbuffet #humor #HackerNews #ngated
Scaling Karpathy's Autoresearch: What Happens When the Agent Gets a GPU Cluster

Karpathy's autoresearch runs one experiment at a time. We gave it access to our GPU infra and let it run experiments in parallel.

SkyPilot Blog
Deep dive into k-CAS: Vesa Karvonen breaks down sweat-free techniques for concurrent, lock-free programming with clear slides and full speaker notes — perfect for systems engineers and PL enthusiasts. Enlightening and practical! #kCAS #Concurrency #LockFree #ParallelComputing #SystemsProgramming #ProgrammingLanguages #VesaKarvonen #Tarides #English
https://watch.ocaml.org/videos/watch/acebc363-12df-4cd6-aec0-e8239ab325e0
k-CAS for sweat-free concurrent programming by Vesa Karvonen

PeerTube
Setting Up A Cluster of Tiny PCs For Parallel Computing - A Note To Myself | Everyday Is A School Day

Enjoyed learning the process of setting up a cluster of tiny PCs for parallel computing. A note to myself on installing Ubuntu, passwordless SSH, automating package installation across nodes, distributing R simulations, and comparing CV5 vs CV10 performance. Fun project!

Everyday Is A School Day
David Lattimore delves into the complexities of parallelizing dynamic graph traversals with Rust's Rayon. His exploration moves beyond fixed workloads, examining iterative approaches: custom work-sharing, scoped spawning, & channel-based solutions. Key insights reveal significant trade-offs involving heap allocations, deadlock risks, and compositional limitations inherent in parallel paradigms. Thoughtful work for those navigating concurrent systems. #RustLang #ParallelComputing #TechEthics

GPU là cốt lõi cho huấn luyện mô hình ngôn ngữ nhờ xử lý song song và tính toán ma trận nhanh. Bài viết phân tích kiến trúc GPU, phân biệt vs CPU, vai trò của CUDA/Tensor Cores, và quản lý VRAM. Hiệu suất GPU được đo lường bằng FLOPS, quyết định tốc độ huấn luyện. #AI #ML #GPU #MôHìnhNgônNgữ #CôngNghệ #ParallelComputing #DeepLearning #CUDA #VRAM #FLOPS #HiểuGPU #MachineLearningVietNam

https://www.reddit.com/r/LocalLLaMA/comments/1pk1hyp/day_4_21_days_of_building_a_small_language/

Unlock GPU acceleration with NVIDIA's cuTile, revolutionizing parallel kernel development #NVIDIA #cuTile #GPUcomputing

NVIDIA's cuTile is a groundbreaking programming model designed to simplify the development of parallel kernels for NVIDIA GPUs, enabling developers to harness the full potential of GPU acceleration. By leveraging cuTile, developers can create high-performance applications that efficiently utilize the massively...

#NVIDIA #cuTile #GPUacceleration #parallelcomputing