#GPU kernel tuning
140 related articles
·3 min
Harness Engineering in Practice: A Guide to Enterprise-Grade Multi-Agent System Architecture
A deep dive into Harness Engineering architecture: building an AI procurement assistant on ERP systems, covering multi-agent orchestration, MCP protocol, ASGI deployment, and sandbox isolation.
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·2 min
Getting Started with LLMs: A Complete Roadmap from Zero to Practice
How to learn LLMs from scratch? This guide covers personalized learning paths for 3 types of learners, hardware tips (16GB RAM is enough), Python prep, and cloud GPU options.
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·3 min
Running Local LLMs on AMD GPUs: Ditching Ollama for LM Studio Delivers 7x Speed Boost
AMD GPU black screens running local LLMs? This post-mortem covers Ollama's 3 fatal flaws and how switching to LM Studio boosted token speed from 5 to 36, with ROCm setup, Speculative Decoding, and GFX version tips.
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Should Frontier AI Models Like GPT-5.6…
·4 min
Should Frontier AI Models Like GPT-5.6 Be Open-Sourced? A Deep Dive into the Open vs. Closed Debate
Should frontier AI models be open-sourced? This deep dive explores the key debates around democratization, misuse risks, commercial sustainability, and governance — and the middle paths between open and closed.
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·7 min
Complete Guide to OpenCode: Installation, Configuration, and Custom Commands in Practice
A systematic guide to OpenCode, the open-source terminal AI coding tool: installation methods (including WSL), model configuration, rules files, Agent types, custom commands, and MCP tool extensions.
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·3 min
Codex APP Deep Dive: Comparison with Claude Code and How to Choose
In-depth comparison of Codex APP vs. Claude Code and Cursor: pricing, stability, and capability differences. Discover Codex's unique strengths in frontend UI development and how to choose the right AI coding tool.
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·4 min
Dify Beginner's Guide: Interface Overview & Complete Docker Self-Hosted Deployment Guide
Complete guide to Dify's four core modules (Explore, Studio, Knowledge Base, Tools) with step-by-step Docker self-hosted deployment instructions for building production-grade AI apps.
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·4 min
Deep Learning Lane Detection: From Segmentation to Classification for 300+ FPS Real-Time Inference
Deep learning lane detection algorithm that simplifies dense segmentation into efficient grid classification, achieving 300+ FPS real-time inference with row selection, Focal Loss, and expectation-based localization.
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·3 min
NVIDIA ACE SDK: On-Device AI Inference for Intelligent Game NPC Companions
Deep dive into NVIDIA ACE Game Agent SDK's integration with Unreal Engine 5, exploring how on-device AI inference enables low-latency, privacy-safe intelligent NPC dialogue and behavior.
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·3 min
DAQIRI Platform Explained: Deep Integration of High-Speed Data Acquisition and Real-Time AI Inference
Deep dive into how the DAQIRI platform embeds NVIDIA GPU-accelerated computing into high-speed data acquisition pipelines, enabling real-time AI inference for industrial inspection, scientific experiments, and autonomous driving.
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·4 min
GLM 5.2 & Zcode Hands-On Review: A Deep Dive into the Free AI Coding Tool with 5 Million Tokens/Day
In-depth review of Zhipu's GLM 5.2 model and Zcode programming tool: interface experience, coding benchmarks, and long-horizon Agent performance compared to GPT and Opus. 5M free tokens/day with MIT license.
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·3 min
PyTorch Image Classification in Practice: Complete Pipeline from Data Preprocessing to Model Training
A PyTorch flower classification project covering the full image classification pipeline: data preprocessing, transforms augmentation, ResNet pretrained models, and Resize strategies with reusable template code.
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·4 min
AI Full-Stack Development Architecture: A Three-Layer Progressive Path from Prototype to Production
A detailed guide to AI full-stack development architecture covering Node.js+TypeScript+Monorepo engineering, Docker CI/CD deployment, and AI engine design with interview tips.
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·3 min
AI Large Model Learning Roadmap Breakdown: Three Stages from Application Development to Model Fine-Tuning
Deep breakdown of a popular AI large model learning roadmap covering LangChain, RAG, Agent, and LoRA fine-tuning across three stages, with analysis of its strengths and limitations for career changers.
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·4 min
Cursor Composer2 Training Revealed: A Complete Guide to Distributed Reinforcement Learning Engineering
Deep dive into how Cursor trained Composer2: two-stage architecture, global distributed clusters, MOE numerical alignment, simulation anti-cheating, and more.
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·3 min
vLLM Deep Dive: How PagedAttention Enables High-Throughput LLM Inference
Deep dive into vLLM's core technologies for high-throughput LLM inference, including PagedAttention memory management, continuous batching, distributed deployment, and comparisons with TensorRT-LLM.
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Tutorials·4 min
Practical Guide to Building a Local AI Knowledge Base with Qwen3.5 + RAGFlow + Ollama
Step-by-step guide to building a local RAG knowledge base using RAGFlow, Ollama, and LM Studio with Docker, covering Embedding model deployment and network troubleshooting for private AI Q&A.
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Product Reviews·4 min
Comprehensive Review of 10 Mainstream AI Coding Tools: How to Choose from Cursor to Claude Code
In-depth comparison of 10 AI coding tools including GitHub Copilot, Cursor, Claude Code, and Windsurf, analyzed across features, target users, and pricing to help developers choose the right AI assistant.
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Research·2 min
Agent Loops in Practice: Transforming Token Output into Productivity from CUDA Kernels to Automated Research
Deep dive into how the Humanize framework transforms LLM tokens into engineering productivity via Agent Loops. Covers KDA winning CUDA kernel contests, virtual hardware optimization, and 50% research cost reduction.
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Industry Insights·2 min
AMD MI355X Beats B200: Full-Stack Optimization Breakdown for 5% Lower TCO on DeepSeek-R1 Inference
AMD Instinct MI355X achieves 5% lower TCO than NVIDIA B200 on DeepSeek-R1 disaggregated inference via SGLang+MoRI full-stack optimization with 1.25x per-GPU throughput.
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