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Show HN: Neurox – GPU Observability for AI Infra

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70% Size, 100% Accuracy: Lossless LLM Compression via Dynamic-Length Float

Next-Gen GPU Programming: Hands-On with Mojo and Max Modular HQ

PyGraph: Robust Compiler Support for CUDA Graphs in PyTorch

CubeCL: GPU Kernels in Rust for CUDA, ROCm, and WGPU

AMD Publishes Open-Source Driver for GPU Virtualization, Radeon "In the Roadmap"

Efficient Code Search with Nvidia DGX

Hopes for cheap 24GB+ cards in 2025

RTX 5080 is about a 3090 but with less VRAM :(

Huawei ClusterMatrix 384 competitor to @NVIDIA's GB200 NVL72

[N] We just made scikit-learn, UMAP, and HDBSCAN run on GPUs with zero code changes! 🚀

Massive 5000 tokens per second on 2x3090

Yes, you could have 160gb of vram for just about $1000.

[D] We’re running 50+ LLMs per GPU by snapshotting GPU memory like a process fork

Nvidia 5060 Ti 16 GB VRAM for $429. Yay or nay?

I built a GPU kernel that sums 100,000+ irregular arrays with no CPU coordination. One call. No reshape. No sync. It just works.

NVIDIA

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k8s-device-plugin

NVIDIA device plugin for Kubernetes

ROCm

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ROCm

AMD ROCm™ Software - GitHub Home

NVIDIA

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open-gpu-kernel-modules

NVIDIA Linux open GPU kernel module source

NVIDIA

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warp

A Python framework for high performance GPU simulation and graphics