remote-compute-ops
FeaturedOperate GPU and remote compute across RunPod (Pods and Serverless), Massed Compute VMs, and owned or virtual remote servers through existing bridges, SSH sessions, MCP/API adapters, bounded polling, cost controls, and resumable lifecycle checks. Use when the user mentions RunPod, Massed Compute, a remote GPU/server/VM, SSH bridge/tunnel/bastion/Tailscale, training or inference on rented compute, GPU inventory, billing, or asks to minimize API/SSH connections and avoid rate limits. Do not use for generic cloud architecture, local-only GPU work, or application code with no remote-resource operation.
Install
Quality Score: 88/100
Skill Content
Details
- Author
- AnastasiyaW
- Repository
- AnastasiyaW/codex-claude-code-config
- Created
- 5 months ago
- Last Updated
- 3 days ago
- Language
- Python
- License
- MIT
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
remote-gpu-trainer
Use whenever the user deploys, trains, monitors, or troubleshoots a long-running GPU job on a RENTED or remote instance they do not own — training, eval, ablation sweeps, batch inference, or large data processing — on AutoDL, RunPod, vast.ai, Lambda, Paperspace, Chinese platforms (恒源云/矩池云/Featurize/揽睿星舟), a bare SSH box, Slurm, or Kubernetes; single OR multi-instance. Triggers (multilingual): "远程 GPU 训练", "GPU 租赁", "GPU rental", "租卡", "spot 抢占", "spot preemption", "断点续训", "resumable training", "tmux 训练守护", "防 SSH 断线", "scp/rsync 上传", "多实例 ablation", "远程 GPU 监控", "省钱关机/销毁实例", "stop vs terminate billing", "checkpoint 磁盘满", "CUDA OOM/显存不足", "loss NaN/loss spike", "loss 不下降/不收敛", "overfit 单 batch", "FSDP/DeepSpeed 配置", "多卡训练 hang", "dataloader worker/数据增广 bug". NOT for purely local single-GPU training, in-instance multi-GPU DDP (use torchrun/accelerate), managed multi-cloud price-shopping (use SkyPilot's skill), or zero-ops serverless (use Modal).
massed-compute-ops
Operate Massed Compute GPU virtual machines through its MCP server. Use when the user mentions Massed Compute, massedcompute, MassedCompute, asks what GPU is available, wants to choose or launch training/inference VMs, inspect running instances, configure SSH access, audit hourly spend or billing runway, restart a VM, or terminate rented compute safely.
remote-gpu-trainer
Use when a user runs, debugs, verifies, or ships a DL experiment on a GPU they OWN or RENT (AutoDL, RunPod, vast.ai, Lambda, Paperspace, 恒源云/矩池云/Featurize/揽睿星舟, bare SSH, Slurm, K8s; single/multi-instance). Triggers (multilingual): 本地训练/local training, 远程 GPU 训练/租卡/GPU rental, spot 抢占/preemption, 断点续训/resumable, 防 SSH 断线/tmux 守护, 多实例 ablation, 关机/销毁/stop-vs-terminate billing, checkpoint 磁盘满, CUDA OOM/显存不足, loss NaN/spike/不收敛, overfit 单 batch, FSDP/DeepSpeed/torchrun, 多卡 hang, 训练太慢/GPU util 低, dataloader/数据增广 bug; 消融结果异常/ablation looks wrong, 复现/reproducibility, 数据泄漏/leakage/test-set tuning, mAP=0/全零指标, 输出恒定/model-ignores-input, train-good/val-collapse, 对比不公平/unfair baseline, 单 seed/no error bars, loss 太好/too-good-to-be-true, 跨文档对账/cross-doc drift; 交付产物/deliverable, 唯一真源/single source of truth, best ckpt 拉回, 结果可视化/论文图脚本, manifest/provenance, 一键复现/repro, EVIDENCE.json. NOT for multi-cloud price-shopping + auto spot-recovery (SkyPilot), BYOC dev environments (dstack), or zero-ops serverless inference (Modal).