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@no_stp_on_snek: Gated delta net prefill was still walking tokens one by one. RDNA3 now does 16-token chunks on WMMA. State stays in the…

X AI KOLs Timeline ↗ · 2026-10-10 Cached

ROCmFPX's gated delta net prefill kernel was optimized to process 16-token chunks via RDNA3 WMMA instead of one token at a time, cutting latency from 772µs to 610µs per 512-token call and improving prompt-processing throughput by ~2-4% across configurations, with Strix Halo testing ongoing.

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#hip

HIP and ROCm as first-class citizens in Guix

Lobsters Hottest ↗ · 2026-10-09

GNU Guix 正式将 AMD 的 HIP 与 ROCm 生态作为一等公民支持,使在 Guix 中进行 AMD GPU 计算栈的功能化打包与部署更加顺畅。

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#hip

ROCm 10.1: Breaking the Data-Movement Bottleneck

Reddit r/LocalLLaMA ↗ · 2026-10-08 Cached

AMD 发布 ROCm 10.1,重点突破数据搬运瓶颈,通过 AMD Infinity Storage (hipFile)、HIP 运行时的 NUMA 感知内存分配以及 ROCm CLI 和 AMD Skills 等开发者工具提升 GPU 数据传输与训练推理效率。

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#hip

AMDKernelVault: Large-Scale Datasets and Agentic Training for AMD GPU Kernel Optimization

arXiv cs.CL ↗ · 2026-09-14 Cached

The article introduces AMDKernelVault, an open dataset and training framework for AMD GPU kernel optimization, featuring large-scale HIP and Triton kernels and agent-driven pipelines for generating and validating kernels.

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#hip

CUDA for AMD on Windows

Hacker News Top ↗ · 2026-09-13 Cached

This tool provides a reproducible Windows setup to run CUDA-targeted applications on AMD GPUs using ZLUDA and AMD HIP/ROCm, validated with RX 9060 XT and LibTorch workloads.

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#hip

CUDA/HIP: Flash Attention tuning (gfx1201) by pwilkin · Pull Request #28102 · ggml-org/llama.cpp

Reddit r/LocalLLaMA ↗ · 2026-09-11 Cached

This pull request introduces Flash Attention tuning optimizations for CUDA/HIP in the llama.cpp project, targeting gfx1201 hardware to enhance inference performance.

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#hip

GLM and I created a llama.cpp fork optimized for AMD GFX906 (Mi50, Mi60, Radeon VII, GCN HIP) - Machine Learning, LLMs, & AI

Reddit r/LocalLLaMA ↗ · 2026-08-22

A fork of llama.cpp has been created and optimized for AMD GFX906 GPUs, improving performance on Mi50, Mi60, Radeon VII, and GCN HIP for machine learning and LLM applications.

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#hip

@AnnmariaKAntony: LLMs are good at CUDA because the internet is full of it. But a model that gives you highly optimized CUDA may still st…

X AI KOLs Timeline ↗ · 2026-07-02 Cached

A multi-agent synthetic data pipeline with SFT and GRPO RL post-training improves HIP compilation and correctness on AMD MI350X GPUs for a 14B open-source model.

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