CUDA
cuda-c9d78948·7 events·first seen 28d agoAliases: CUDA
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Custom CUDA Kernels for All from Codex and Claude
A Hugging Face blog post describes using AI coding agents (Codex and Claude) to automatically generate custom CUDA kernels, lowering the barrier to GPU kernel development. The piece demonstrates agent-assisted GPU programming as a practical workflow for ML practitioners. This represents a concrete application of AI coding tools to the specialized domain of CUDA/GPU optimization.
We Got Claude to Build CUDA Kernels and Teach Open Models
A Hugging Face blog post describes using Claude to generate CUDA kernels and then distilling that knowledge into open-weight models. The approach combines LLM-assisted low-level GPU programming with knowledge transfer to smaller open models. This sits at the intersection of AI-assisted systems programming and open-weights capability improvement.
From Zero to GPU: A Guide to Building and Scaling Production-Ready CUDA Kernels
Hugging Face published a guide on building and scaling production-ready CUDA kernels, covering the full workflow from development to deployment. The post targets ML engineers who need to write custom GPU kernels for inference optimization and production workloads. It addresses practical concerns around kernel compilation, testing, and integration with existing ML frameworks.
Import AI 448: AI R&D; ByteDance's CUDA-writing agent; on-device satellite AI
Import AI issue 448 covers several AI/ML developments including an AI R&D theme, ByteDance's agent capable of writing CUDA code, and on-device AI for satellite applications. The newsletter also raises the question of when AI will play a decisive role in military conflict, drawing an analogy to drone warfare in Ukraine. The body provided is a teaser excerpt; full content covers multiple technical and strategic topics.
Introducing Triton: Open-source GPU programming for neural networks
OpenAI released Triton 1.0, an open-source Python-like language for GPU programming targeting neural network workloads. It enables researchers without CUDA expertise to write highly efficient GPU kernels, reportedly matching expert-level performance in most cases. The release lowers the barrier to custom GPU kernel development for ML practitioners.
Hugging Face Launches Kernel Hub for Custom GPU Kernels
Hugging Face has introduced the Kernel Hub, a centralized repository for sharing and discovering custom GPU kernels optimized for AI/ML workloads. The platform aims to make high-performance custom CUDA and Triton kernels more accessible to the broader ML community. This represents an infrastructure layer addition to the Hugging Face ecosystem, complementing its existing model and dataset hubs.
Run a ChatGPT-like Chatbot on a Single GPU with ROCm
Hugging Face published a guide demonstrating how to run a large language model chatbot on a single AMD GPU using ROCm, AMD's open-source GPU compute stack. The post covers setup, model loading, and inference on AMD hardware as an alternative to NVIDIA CUDA-based workflows. This is relevant to the growing interest in democratizing LLM inference beyond NVIDIA's ecosystem.