DevTeam GPU Scheduler
0.58已归档59 次浏览0 次认可5/9/2026
AI InfrastructureDeveloper ToolsRemote Teams
来源平台: idea-spark
A dead-simple web dashboard for small, remote AI/ML teams (2-8 people) to view, book, and share access to their pooled GPU servers. Solves constant conflicts over who is using which machine and when, eliminating workflow downtime.
目标用户
Small remote teams of 2-8 AI/ML researchers or developers who share a pool of 2-10 physical or cloud GPU instances (e.g., on AWS, GCP, or on-prem servers).
核心差异点
Zero-config status detection for common cloud/on-prem GPU setups. Unlike complex MLOps platforms, it's just a shared calendar for your GPUs—solves the single pain point of 'who's using the A100 right now?' in 5 minutes.
解决方案
A lightweight web app (Next.js, Tailwind) that uses SSH/HTTP pings to detect GPU server status (idle/busy). Users log in, see a calendar view of all servers, and click to book a time slot. Core backend (Python/FastAPI) manages bookings and sends Slack/Discord notifications. No complex orchestration, just a shared calendar for expensive hardware.
关联痛点
Small remote AI/ML teams lack systems to effectively share and manage GPU resources causing workflow conflicts.
MVP 范围
Dashboard showing real-time status (idle/busy) for manually added GPU servers via IP/SSH key
Simple calendar view to create
view
and delete bookings for each server
Basic Slack/Discord webhook notifications for new bookings and upcoming reservations