gpu-cluster

Resource scheduling and cluster management for AI

Best practices & guides on how to write distributed pytorch training code

Mimir — 一站式科研工作台插件：LaTeX 论文边写边编译、arXiv 文献管理、实验追踪、指标图表、GPU 服务器 SSH 任务编排，管理科研全周期。An open-source research workbench plugin for the whole research cycle.

A declarative workflow orchestrator for massive GPU clusters of any kind, including slurm, K8S and docker. Topology-aware node and GPU placement, multi-node replicas and sweeps, readiness/failure probes, and batch submission — so one descriptor drives hundreds of GPUs instead of a pile of hand-written bash.

Mixed-vendor GPU inference cluster manager with speculative decoding

AI动力(AI Power) GPU云平台使用指南

qihoo360 xlearning with GPU support; AI on Hadoop

GPU management System on Kubernetes For AI, Deep-Learning, Machine-Learning Researcher.

Example code for deploying GPU workloads on ECS

Complete setup guide for a 2-node NVIDIA DGX Spark cluster — distributed training, CUDA inference with EXO, NCCL tuning for Grace Blackwell, NVMe-TCP shared storage, and 200 Gb/s direct fabric networking.

Open-source GPU operator agent for the Scalattice inference network (Rust).

Project "Springfield"

Turn a DGX Spark GPU cluster into a self-running team of specialized AI agents — cluster control, role-specialized workers, and an autonomous review gate for Hermes

Detailed Analysis Traces for AI jobs leveraging spot GPU resources

Audit GPU cluster communication schedules from NCCL logs. Zero dependencies. CI-ready.

Web UI for orchestrating distributed llama.cpp RPC GPU clusters with auto node discovery, telemetry, and one-click deployment.

Generate reproducible deep-learning workload traces by mapping production GPU-cluster traces to profiled executable workloads.

Docker Images for the GPU Cluster

Official artifact for MoSim, a trace-driven GPU-cluster simulator with dynamic network contention modeling (IEEE MASCOTS 2026).