Resource scheduling and cluster management for AI
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Updated
Oct 18, 2026 - JavaScript
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
qihoo360 xlearning with GPU support; AI on Hadoop
GPU management System on Kubernetes For AI, Deep-Learning, Machine-Learning Researcher.
Self-hosted GPU cluster orchestration: deploy and serve open-source AI models on your own hardware — FastAPI control plane, worker agents, vLLM/SGLang engines and an OpenAI-compatible gateway.
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.
GPU operator agent for the Scalattice inference network (Rust).
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
Project "Springfield"
Official artifact for MoSim, a trace-driven GPU-cluster simulator with dynamic network contention modeling (IEEE MASCOTS 2026).
Audit GPU cluster communication schedules from NCCL logs. Zero dependencies. CI-ready.
Detailed Analysis Traces for AI jobs leveraging spot GPU resources
Web UI for orchestrating distributed llama.cpp RPC GPU clusters with auto node discovery, telemetry, and one-click deployment.
A reproducible comparison of Kubernetes GPU schedulers (Kueue, Volcano, KAI) on identical workload traces — kwok-simulated GPU fleet, runs on a laptop.
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