--- id: "/tags/infrastructure-chips-efficiency/page/3/" title: "Infrastructure Chips Efficiency · page 3" url: "https://skillissue.dev/tags/infrastructure-chips-efficiency/page/3/" --- # Infrastructure Chips Efficiency [Beginner](/levels/beginner/index.md) [Intermediate](/levels/intermediate/index.md) [Advanced](/levels/advanced/index.md) [Expert](/levels/expert/index.md) 122 resources · page 3 of 4 - ### [google-ai-edge/gallery: skills](/model-training/training-infrastructure/google-ai-edge-gallery-skills/index.md) by [google-ai-edge](https://github.com/google-ai-edge) Google AI Edge Gallery skills folder on GitHub: skills for on-device ML and generative AI apps. Intermediate learning_resource skill-library US en - ### [Google TPU docs](/model-training/training-infrastructure/google-tpu-docs/index.md) by [Google Cloud](https://cloud.google.com/) Google Cloud TPU documentation for running machine-learning training and inference on Tensor Processing Units. Intermediate–Advanced learning_resource docs US en - ### [GPU MODE](/model-training/training-infrastructure/gpu-mode/index.md) by [GPU MODE community](https://www.gpumode.com/) GPU MODE site: community for learning GPU programming through lectures, hackathons, kernel competitions and working groups. Intermediate–Advanced learning_resource course Global en - ### [GPU MODE lectures](/model-training/training-infrastructure/gpu-mode-lectures/index.md) by [GPU MODE](https://github.com/gpu-mode) GPU MODE lectures GitHub repo: slides and code from community lectures on GPU programming and CUDA kernels. Intermediate–Advanced learning_resource course Global en - ### [GPU MODE resource stream](/model-training/training-infrastructure/gpu-mode-resource-stream/index.md) by [GPU MODE](https://github.com/gpu-mode) GPU MODE resource-stream GitHub repo: curated links to CUDA and GPU programming books, papers, posts and videos. Intermediate learning_resource guide Global en - ### [Groq blog](/model-training/training-infrastructure/groq-blog/index.md) by [Groq](https://groq.com/) Groq blog with posts on its LPU inference hardware, cloud API and supported models. Intermediate learning_resource blog US en - ### [Groq documentation](/model-training/training-infrastructure/groq-documentation/index.md) by [Groq](https://groq.com/) Groq documentation: OpenAI-compatible API, available models and rate limits for its LPU inference service. Intermediate learning_resource docs US en - ### [Making Deep Learning Go Brrrr From First Principles (Horace He)](/model-training/training-infrastructure/horace-he-making-dl-go-brrrr/index.md) by [Horace He](https://horace.io/) Horace He's Making Deep Learning Go Brrrr: first-principles guide to whether models are compute-, memory- or overhead-bound. Intermediate learning_resource guide US en - ### [vLLM documentation](/model-training/training-infrastructure/inference-serving-quantization/index.md) by [vLLM project](https://vllm.ai/) vLLM documentation: open-source engine for high-throughput LLM inference and serving. Intermediate–Advanced learning_resource docs US en - ### [LM Studio blog](/model-training/training-infrastructure/lm-studio-blog/index.md) by [LM Studio](https://lmstudio.ai/) LM Studio blog with release notes and technical posts on running LLMs locally. Intermediate learning_resource blog US en - ### [Modal blog](/model-training/training-infrastructure/modal-blog/index.md) by [Modal](https://modal.com/) Modal blog on serverless GPU computing, infrastructure engineering and running AI workloads. Intermediate learning_resource blog US en - ### [Ollama blog](/model-training/training-infrastructure/ollama-blog/index.md) by [Ollama](https://ollama.com/) Ollama blog with release notes, supported model announcements and guides for running models locally. Intermediate learning_resource blog US en - ### [OpenRouter docs: Prompt Caching](/model-training/training-infrastructure/openrouter-prompt-caching/index.md) by [OpenRouter](https://openrouter.ai/) OpenRouter guide to prompt caching across model providers, with cost implications. Intermediate learning_resource docs US en - ### [PyTorch FSDP tutorial](/model-training/training-infrastructure/pytorch-fsdp-tutorial/index.md) by [PyTorch Foundation](https://pytorch.org/) PyTorch tutorial on Fully Sharded Data Parallel (FSDP2) for training large models across GPUs. Intermediate–Advanced learning_resource docs US en - ### [Qwen 中文文档](/model-training/training-infrastructure/qwen/index.md) by [Qwen (Alibaba)](https://qwen.ai/) Qwen documentation in Chinese: usage, deployment and fine-tuning of Qwen language and multimodal models. Intermediate learning_resource docs China zh - ### [SGLang documentation](/model-training/training-infrastructure/sglang/index.md) by [SGLang project (LMSYS)](https://lmsys.org/) SGLang documentation: serving framework for large language and multimodal models. Intermediate–Advanced learning_resource docs US en - ### [Together AI blog](/model-training/training-infrastructure/together-ai-blog/index.md) by [Together AI](https://together.ai/) Together AI blog with product launches, research and technical guides on inference, fine-tuning and GPU clusters. Intermediate learning_resource blog US en - ### [Transformers documentation](/model-training/training-infrastructure/transformers-documentation/index.md) by [Hugging Face](https://huggingface.co/) Hugging Face Transformers documentation: reference for model architectures, loading, training and generation. Intermediate learning_resource docs US; France; international en - ### [Triton Puzzles](/model-training/training-infrastructure/triton-puzzles/index.md) by [GPU MODE](https://github.com/gpu-mode) Triton Puzzles GitHub repo: interactive exercises for learning to write GPU kernels in Triton. Intermediate learning_resource course US en - ### [Triton tutorials](/model-training/training-infrastructure/triton-tutorials/index.md) by [OpenAI (Triton)](https://triton-lang.org/) Triton tutorials: ordered examples from vector addition to fused softmax, matmul and fused attention GPU kernels. Intermediate–Advanced learning_resource docs US en - ### [Unsloth blog](/model-training/training-infrastructure/unsloth-blog/index.md) by [Unsloth AI](https://unsloth.ai/) Unsloth blog with guides and release notes for fast, memory-efficient LLM fine-tuning. Intermediate learning_resource blog US en - ### [A graph placement methodology for fast chip design](/model-training/training-infrastructure/alphachip-mirhoseini-et-al-nature-2021/index.md) by [Azalia Mirhoseini et al. (Google)](https://ai.google/) Nature paper (2021) by Mirhoseini et al. introducing the reinforcement learning chip floorplanning method later named AlphaChip. Advanced learning_resource paper US en - ### [Agentic inference optimization (Baseten)](/model-training/training-infrastructure/baseten-agentic-inference-optimization/index.md) by [Baseten](https://baseten.co/) Baseten post on optimising inference engines for agent workloads, reporting decode-speed and latency gains over vLLM. Advanced learning_resource blog US en - ### [Baseten documentation](/model-training/training-infrastructure/baseten-documentation/index.md) by [Baseten](https://www.baseten.co/) Baseten documentation for running hosted models, deploying custom models and training on GPU infrastructure. Advanced learning_resource docs US en - ### [BentoML documentation](/model-training/training-infrastructure/bentoml-documentation/index.md) by [BentoML](https://www.bentoml.com/) BentoML documentation: open-source inference platform for packaging, deploying and scaling AI models. Advanced learning_resource docs US/global en - ### [Code execution with MCP](/model-training/training-infrastructure/code-execution-with-mcp/index.md) by [Anthropic](https://anthropic.com/) Anthropic post on code execution with MCP: agents write code to call tools, reducing token use and context load. Advanced learning_resource guide US en - ### [Defeating Nondeterminism in LLM Inference](/model-training/training-infrastructure/defeating-nondeterminism-in-llm-inference/index.md) by [Thinking Machines Lab](https://thinkingmachines.ai/) Thinking Machines Lab post on the causes of nondeterminism in LLM inference and batch-invariant kernels to fix it. Advanced learning_resource paper US en - ### [DoWhy documentation](/model-training/training-infrastructure/dowhy-2/index.md) by [PyWhy](https://www.pywhy.org/) DoWhy documentation: Python library for causal inference with modelling, identification, estimation and refutation steps. Advanced learning_resource docs Global en - ### [EconML](/model-training/training-infrastructure/econml/index.md) by [PyWhy](https://www.pywhy.org/) EconML documentation: Python methods for estimating heterogeneous treatment effects with machine learning. Advanced learning_resource docs US; international en - ### [Feast documentation](/model-training/training-infrastructure/feast-documentation/index.md) by [Feast project](https://feast.dev/) Feast documentation: open-source feature store for serving consistent features to ML training and inference. Advanced learning_resource docs Global en - ### [Fireworks AI documentation](/model-training/training-infrastructure/fireworks-ai-documentation/index.md) by [Fireworks AI](https://fireworks.ai/) Fireworks AI documentation: serverless and dedicated inference, fine-tuning and deployment of open models. Advanced learning_resource docs US en - ### [Three Tests to Run Before You Switch from LoRA to FullFT (Fireworks AI)](/model-training/training-infrastructure/fireworks-three-tests-before-you-switch-from-lora-to-fullft/index.md) by [Fireworks AI](https://fireworks.ai/) Fireworks AI post with controlled experiments on Qwen3.5-9B showing what to test before switching from LoRA to full fine-tuning. 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