基于agent时代的quant平台

AI-assisted TradingView chart analysis — connect Claude Code to your TradingView Desktop for personal workflow automation

An agent-managed museum exhibit, built in Rust with Gajae-Code / LazyCodex — developed and maintained with no human intervention.

FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-makin…

Kronos: A Foundation Model for the Language of Financial Markets

OpenStock is an open-source alternative to expensive market platforms. Track real-time prices, set personalized alerts, and explore detailed company insights — built openly, for everyone, forever f…

Claude Code 中文全面上手指南。基于 luongnv89/claude-howto 本土化重写，面向中国小白用户，保留命令与配置兼容性，并附学习路径与本地化校验护栏。

Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflo…

基于多智能体LLM的中文金融交易框架 - TradingAgents中文增强版

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost…

from vibe coding to agentic engineering - practice makes claude perfect

An official lightweight library for the RaBitQ algorithm and its applications in vector search.

HyFlexPIM noise-aware simulator

Mapper for digital PIM architectures

[KDD 2026] FuXi-𝛾: Efficient Sequential Recommendation with Exponential-Power Temporal Encoder and Diagonal-Sparse Positional Mechanism

A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores

An accelerator for high-dimensional approximate nearest neighbor search

including compiler to encode DGL GNN model to instructions, runtime software to transfer data and control the accelerator, and hardware verilog code that can be implemented on FPGA

CNN accelerator implemented with Spinal HDL

Reference implementations of MLPerf® inference benchmarks

Reference implementations of MLPerf® training benchmarks

Official implementation of "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training"

Official implementation of "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training"

Benchmark AMD CPU/GPU performance on GNN workload

Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass

Profiling and benchmarking Pytorch operations relevant to SOTA graph neural network architectures

[ASAP 2020; FPGA 2020] Hardware architecture to accelerate GNNs (common IP modules for minibatch training and full batch inference)