Development repository for the Triton language and compiler
A migration benchmark that measures whether production GPU Triton kernels — extracted from vLLM and SGLang inference paths — can be ported to the Huawei Ascend 910B (Atlas A2) via `triton-ascend` without losing correctness or performance.
LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.
SparkDiffusion: Accelerating DiT video generation by 265× via joint Sparsity, Distillation, Quantization, etc.
LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalability, and high-speed performance.
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Triton is a dynamic binary analysis library. Build your own program analysis tools, automate your reverse engineering, perform software verification or just emulate code.
For more information, please see http://smartos.org/ For any questions that aren't answered there, please join the SmartOS discussion list: https://smartos.topicbox.com/groups/smartos-discuss
FlagGems is an operator library for large language models implemented in the Triton Language.
Triton's Dragon's Mouth Yellowstone gRPC service for high-performance Solana streaming
The Triton TensorRT-LLM Backend
This repository contains tutorials and examples for Triton Inference Server
Trainable fast and memory-efficient sparse attention
LLM algorithm practice lab with theory, solutions, and test cases.《大模型算法与系统教程》面向大模型入门到进阶的算法实战教程,覆盖原理讲解、答案解析、测试用例与 CUDA/Triton 实战。
Triton Python, C++ and Java client libraries, and GRPC-generated client examples for go, java and scala.
Triton backend that enables pre-process, post-processing and other logic to be implemented in Python.
Linux kernel module to support Turbo mode and RGB Keyboard for Acer Predator notebook series
From teacher to tiles — a from-scratch LLM distillation & serving engine: custom Triton/CUDA kernels, FSDP distillation, paged-KV continuous batching, speculative decoding, a Rust gateway, a JAX oracle, and interpretability tooling.
Triton Model Analyzer is a CLI tool to help with better understanding of the compute and memory requirements of the Triton Inference Server models.
Open Model Engine (OME) — Kubernetes operator for LLM serving, GPU scheduling, and model lifecycle management. Works with SGLang, vLLM, TensorRT-LLM, and Triton
A toolkit for AI agents used for development on Triton-Ascend for Ascend NPU
NVIDIA Sol-Attn for ComfyUI / Triton kernel on SM89 - SM121, with zero-copy MiniMax H3 nodes: memory-efficient attention, scheduled tau with graph preview, and feed-forward chunking. Measured 1.14–1.44× vs SageAttention and −37% MLP peak VRAM on H3
GPU 性能与 AI Infra 学习项目:CUDA/Triton 算子、NCU/NSYS、vLLM/SGLang/TRT-LLM/ms-swift、PyTorch/DeepSpeed/ms-swift 训练、并行架构
A Mini-vLLM optimization project for Qwen3-32B TP=2 serving, Prefix Cache, and Triton PagedAttention.
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Large language model systems implementation and optimization: Transformers, BPE tokenization, FlashAttention, Triton, distributed training, GPU profiling, and GRPO reasoning RL
Production-ready CosyVoice serving with Triton, reusable Speaker Registry, Public HTTP API and Web console.
MiniMax-H3 33B audio+video DiT accelerated 1.54x on a single NVIDIA DGX Spark (GB10, sm_121): NVIDIA Sol-Engine FirstBlockCache + batched VAE decode ported to single-GPU ComfyUI, Sol-Attn patched for compute 12.1, kijai Triton INT8/TMA kernels. Benchmarks, charts, one-shot installer, agent recipe.
Lean 4 framework for reasoning about Triton-style kernels.
Efficient Triton Kernels for LLM Training
Add bisenetv2. My implementation of BiSeNet
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