Mastodawn

🎉🥳 Behold the modern marvel: 100 Claude agents, meticulously choreographed to dance in parallel, all under the command of the almighty "mngr." Sure, it's the future of software development, but let's not forget it's really just a flashy way to say "look, Ma, no hands!" 🙄✨
https://imbue.com/product/mngr_part_2/ #modernsoftwaredevelopment #parallelprocessing #Claudeagents #automation #marvels #HackerNews #ngated

A case study in testing with 100+ of Claude agents in parallel

In our previous blog post, we introduced mngr and how you can use it to usefully launch hundreds of parallel agents. Here’s all the details…

Hacker News 1d ago

A case study in testing with 100+ Claude agents in parallel

https://imbue.com/product/mngr_part_2/

#HackerNews #A #case #study #in #testing #with #100+ #Claude #agents #in #parallel #ClaudeAgents #Testing #CaseStudy #AI #ParallelProcessing

A case study in testing with 100+ of Claude agents in parallel

In our previous blog post, we introduced mngr and how you can use it to usefully launch hundreds of parallel agents. Here’s all the details…

NewsletterTF 5d ago

SHIFTING CURRENTS IN COMPUTATIONAL LATTICES

New NVIDIA CUDA Toolkit 12.2 features improve Python GPU programming. Learn how this helps developers run complex calculations faster on NVIDIA GPUs.

#NVIDIACUDA, #GPUcomputing, #PythonDev, #TechUpdate, #ParallelProcessing

https://newsletter.tf/nvidia-cuda-toolkit-12-2-python-gpu-computing/

NewsletterTF 5d ago

NVIDIA's CUDA Toolkit 12.2 is out, offering new tools that make running complex calculations on GPUs much easier for Python developers.

#NVIDIACUDA, #GPUcomputing, #PythonDev, #TechUpdate, #ParallelProcessing
https://newsletter.tf/nvidia-cuda-toolkit-12-2-python-gpu-computing/

NVIDIA CUDA Toolkit 12.2 Updates Boost Python GPU Computing

New NVIDIA CUDA Toolkit 12.2 features improve Python GPU programming. Learn how this helps developers run complex calculations faster on NVIDIA GPUs.

NewsletterTF

N-gated Hacker News Mar 21

🚀 Oh, behold the tale of Ironkernel: where #Python dons a Rusty suit and claims to unlock the mystical powers of parallel processing. 🤖 GitHub's latest offering promises to make your CPU cores work overtime, while you contemplate the deep existential question: "Will #AI ever replace my need to understand this sorcery?" 🧙‍♂️✨
https://github.com/YuminosukeSato/ironkernel #Ironkernel #Rust #ParallelProcessing #GitHub #HackerNews #ngated

GitHub - YuminosukeSato/ironkernel: Python DSL that compiles element-wise expressions to parallel Rust. All CPU cores, zero serialization.

Python DSL that compiles element-wise expressions to parallel Rust. All CPU cores, zero serialization. - YuminosukeSato/ironkernel

GitHub

SESH.sx Mar 13

Drums@Work: Techno Edition - 14 Mar feat. Blint, Parallel Processing, Migz + more

#SESH #Blint #ParallelProcessing #Migz

https://sesh.sx/e/1907189

SESH.sx Mar 9

Blank Pages presents: PAGE SEVEN @ arkaoda Berlin - 11 Mar feat. Parallel Processing, Migz

#SESH #ParallelProcessing #Migz

https://sesh.sx/e/1894086

AI Daily Post Feb 23

Explore how LangGraph leverages JSON schemas and shared state to orchestrate multi‑agent AI. Learn the design patterns that let agents coordinate, sync data, and run in parallel—making complex workflows reliable and open‑source ready. #LangGraph #AIAgents #SharedState #ParallelProcessing

🔗 https://aidailypost.com/news/design-patterns-use-json-shared-state-coordinate-agentic-ai

AI Daily Post Feb 2

OpenAI just dropped a macOS app that lets multiple AI coding agents run side‑by‑side, boosting parallel processing for developers. It promises faster code generation, but also raises new cybersecurity questions around code manipulation. Dive into how Codex is reshaping open‑source tooling and what this means for your projects. #AICoding #Codex #OpenAI #ParallelProcessing

🔗 https://aidailypost.com/news/openai-launches-codex-macos-app-run-multiple-ai-coding-agents-parallel

Dr Micha Campbell Feb 2

Has anyone got any experience in #ParallelProcessing in R?

I'm running hysplit trajectories (wrapped in a tryCatch) in parallel using parLapply from {parallel}, and they are failing intermittently - in a list of 10, one or as many as 4 will run OK, but the rest will return NAs. When I run them separately, they run correctly.

The data are in an external drive, could that be the issue?

Very open to suggestions!

#RStats