Frameworks & Training

PyTorch, TensorFlow, JAX, datasets, and accelerator workflows.

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marktechpost.com > 09/14/2026 > sakana-ai-researchers-introduce-pc-alm-a-layer-local-alternative-to-backpropagation-that-trains-1000-layer-networks

Sakana AI Researchers Introduce PC-ALM, a Layer-Local Alternative to Backpropagation That Trains 1000-Layer Networks

27+ min ago   (169+ words) Is it deployable? Yes, as research code: an MIT-licensed JAX reference implementation runs on CPU and reproduces the paper’s width-depth grid. It is a training method, not a model, and has only been tested on small image benchmarks. LeCun observed…...


hackaday.com > 09/14/2026 > pulse-a-new-vhdl-simulator

Pulse: A New VHDL Simulator

10+ hour, 38+ min ago   (35+ words) With VHDL being arguably more deterministic and bullet-proof than Verilog, it's good to see another open source VHDL simulator joining the fray that is not a variation of ghdl. Written by [Óscar Grim......


medium.com > @patelulka0229 > gradient-descent-a-beginners-complete-guide-to-how-machines-learn-02b57751bbbc

Gradient Descent: A Beginner’s Complete Guide to How Machines Learn

1+ day, 18+ min ago   (414+ words) If you’ve started learning Machine Learning, you’ve probably come across the term Gradient Descent. It may sound mathematical …...


marktechpost.com > 09/12/2026 > implementation-of-machine-learning-workflows-with-nvidia-cuml-rapids-gpu-benchmarking-explainability-clustering-and-model-inference

Implementation of Machine Learning Workflows with NVIDIA cuML, RAPIDS, GPU Benchmarking, Explainability, Clustering, and Model Inference

1+ day, 19+ hour ago   (198+ words) We benchmark scikit-learn and cuML implementations of PCA, K-Means, nearest neighbors, logistic regression, random forests, and DBSCAN. We generate datasets on the GPU, synchronize CUDA operations for fair timing, and record the speedup each accelerated algorithm achieves. We also compare…...


dev.to > anovisoft > rendering-live-broadcast-graphics-without-a-gpu-and-what-four-hours-actually-cost-3c9l

Rendering live broadcast graphics without a GPU, and what four hours actually cost

2+ day, 9+ hour ago   (683+ words) Short recap, because this is the second half of a story. In the previous article I described how our... Tagged with devops, architecture, performance, programming....


dev.to > rosgluk > rocm-vs-vulkan-for-amd-local-llm-hosting-2026-guide-5c70

ROCm vs Vulkan for AMD Local LLM Hosting: 2026 Guide

2+ day, 9+ hour ago   (1662+ words) ROCm and Vulkan both accelerate AMD GPUs for local LLM hosting, but they are not interchangeable. The right choice depends on the engine, GPU, and workload. In local LLM hosting the two backends sit at different layers. ROCm is AMD's…...


phoronix.com > news > Erik-Faye-Lund-Mesa-Arm

Prominent Mesa Developer Now Working For Arm On PanVK & Panfrost Code

3+ day, 8+ hour ago   (207+ words) Erik Faye-Lund who has contributed to the Mesa 3D graphics driver stack working on areas like Zink and most notably the PanVK Vulkan and Panfrost Gallium3D drivers forr Arm Mali hardware is now working directly for Arm... - Categories Computers Display Drivers Graphics…...


hpcwire.com > off-the-wire > ciq-moves-rlc-pro-ai-to-linux-6-18-to-improve-ai-infrastructure-performance

CIQ Moves RLC Pro AI to Linux 6.18 to Improve AI Infrastructure Performance

3+ day, 18+ hour ago   (543+ words) RENO, Nev., Sept. 10, 2026 — CIQ, the founding support and services partner of Rocky Linux, today moved RLC Pro AI to Linux 6.18, the latest long-term kernel. Enterprises get the latest kernel features with a vendor standing behind them, and the same tuned…...


linux-magazine.com-magazine.com

AI Fixes Linux Bottlenecks Using “Hideous” Code » Linux Magazine

4+ day, 1+ hour ago   (555+ words) In that same email, Stoakes stated that he used an LLM to determine where the bottlenecks were and how to improve them. He then said that the LLM generated a lot of code, "much of it hideous." "The patches work…...


dev.to > gde > gemma-4-on-an-old-4-gb-laptop-gpu-qat-takes-it-from-95-gib-to-16-b5l

Gemma 4 on an Old 4 GB Laptop GPU: QAT Takes It From 9.5 GiB to 1.6

4+ day, 2+ hour ago   (1449+ words) This article provides a step by step deployment guide for Gemma 4 E2B's quantization-aware-trained (QAT) checkpoint to a local, laptop hosted GPU enabled system — a much older Lenovo Yoga 9 with a 4 GB GTX 1650 Ti. A suite of Python MCP tools is…...