A curated list of best cuda programming books
Real-time stream editing pipeline powered by the FLUX.2-klein-4B model, optimized for consumer GPUs
A GPU-Accelerated First-Order LP Solver
Personal CUDA learning repo, built step by step from scratch.
The intelligent OptiScaler installer Linux gamers needed. Automates FSR4, XeSS & DLSS configuration with GPU-optimized profiles for RDNA3/4, Arc & RTX cards.
GVProf: A Value Profiler for GPU-based Clusters
Boost Valheim's FPS to forge a smoother Viking journey!
Fast waifu2x converter with GPU optimization
Fast waifu2x converter with GPU optimization
Handwritten Flash Attention 2 CUDA kernel for Blackwell (SM120) with TMA, swizzle, double buffering & warp specialization
Production-ready checklists and frameworks for deploying LLMs, GenAI models, and AI infrastructure. Covers vLLM, Kubernetes, GPU optimization, observability, compliance, and Day-0 to Day-2 operations.
KeSSie HUGE Context Semantic recall for Large Language Models
The GPU Optimizer for ML Models enhances GPU performance for machine learning. It offers advanced scheduling, real-time monitoring, and efficient resource management through a user-friendly web interface and robust API, integrating big data technologies for seamless data processing and model optimization. @NVIDIA
Bilingual CUDA SGEMM optimization tutorial and reference implementation, from naive kernels to Tensor Core WMMA | 双语 CUDA SGEMM 优化教程与参考实现，从朴素内核到 Tensor Core WMMA
A high-performance C++ backend for extreme-context LLM inference. It replaces item-count batching with dynamic, VRAM-aware First-Fit Decreasing (FFD) bin packing. By using PyBind11 for async queueing, 16-token alignment, and `cudaHostAlloc` for zero-copy FlashAttention-2 transfers, it mathematically eliminates OOMs and maximizes GPU throughput.
Windows 10\11 optimizer
First open-source real-time face filter app using MediaPipe FaceMesh for high-performance, GPU-accelerated effects.
Executive FinOps dashboard and automated governance engine using FOCUS 1.3 standards for AWS, Azure, and Snowflake.
Physics-based computation at scale — Hamiltonian dynamics, spectral theory, and statistical mechanics powering optimization, drug discovery, genomics, molecular proof, and agentic commerce.
用于复现和优化常见的深度学习算子，基于cuda和triton两种方案，可供学习和参考
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