Distributed
34 items across the graph — tagged with Distributed.
From the graph · 34
An Open Source Machine Learning Framework for Everyone
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, Slurm, 20+ clouds, on-prem).
Build, Manage and Deploy AI/ML Systems
Democratizing Reinforcement Learning for LLMs
High-performance data engine for AI and multimodal workloads. Process images, audio, video, and structured data at any scale
Achieve state of the art inference performance with modern accelerators on Kubernetes
High-Performance Symbolic Regression in Python and Julia
Drop-in Apache Spark replacement written in Rust, unifying batch processing, stream processing, and compute-intensive AI workloads.
Distributed AI Model Training and LLM Fine-Tuning on Kubernetes
The first distributed AGI system. Thousands of autonomous AI agents collaboratively train models, share experiments via P2P gossip, and push breakthroughs here.…
🧭 Architecture-first system design: 26 bilingual tutorials, 25 architecture templates, and 6 end-to-end cases covering distributed systems, AI-native systems,…
Ultrafast serverless GPU inference, sandboxes, and background jobs
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Distributed AI/LLM for the people. Share compute privately or publicly to power your agents and chat.
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
SDK libraries for Modal
An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale
Self-hosted AI agent OS. Your memory, chat, agents, and files stay on hardware you own, offline by default, cloud by choice. Offline AI memory (taOSmd), self-ho…
Fastest Robotics Runtime System. If phones have Android, robots deserve HORUS.
High Performance Data Processing in Python
📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…
A lightweight runtime health check for PyTorch training runs.
This is the Docker container based on open source framework XGBoost (https://xgboost.readthedocs.io/en/latest/) to allow customers use their own XGBoost scripts…
Universal Python SDK to run AI workloads on Kubernetes
Provider-neutral control plane for durable-state agent swarms: subprocess workers, leases, artifacts, memory, and deterministic stitching.
Machine learning library, Distributed training, Deep learning, Reinforcement learning, Models, TensorFlow, PyTorch
OpenTelemetry instrumentation for RubyLLM. 💬🔭
Research platform for model training, evaluation, and experimentation across architectures, benchmarks, and recipes.
A Go framework for the microagents architecture with dynamic discovery — specialized agents and tools that register their capabilities with a shared registry, f…
Test LightGBM's Dask integration on different cluster types