Boost Developer Productivity with NBD VRAM, Reg Factory, and vLLM Studio

This article introduces three open‑source tools that improve GPU‑centric development: NBD VRAM, which turns GPU memory into Linux swap space; Reg Factory, a scheduler and monitor for multi‑GPU clusters; and vLLM Studio, a web UI for deploying and managing large‑model inference.

Geek Labs
Geek Labs
Geek Labs
Boost Developer Productivity with NBD VRAM, Reg Factory, and vLLM Studio

Today we share three open‑source projects that aim to increase developer efficiency when working with GPUs.

NBD VRAM – Using GPU Memory as System Swap

NBD VRAM is an inventive project that converts your GPU's video memory into Linux swap space. It leverages the Network Block Device (NBD) mechanism to expose VRAM as block devices, which can then be mounted as a swap partition.

# Install
pip install nbd-vram
# Start
nbd-vram --size 4G --device /dev/nbd0
# Enable swap
sudo swapon /dev/nbd0

The tool is suitable for scenarios where VRAM is abundant but system RAM is limited, such as running large models on a Mac with 64 GB VRAM and only 16 GB RAM, or on GPU servers that have idle video memory.

GitHub: https://github.com/c0deJedi/nbd-vram<br/>Stars: 300+ | Language: Python | License: MIT
NBD VRAM project homepage
NBD VRAM project homepage

Reg Factory – GPU Resource Scheduling and Management

Reg Factory is a GPU resource scheduling and management tool designed for teams that operate multi‑GPU servers. It supports job queuing, resource allocation, monitoring, and alerting.

Queueing and scheduling of multi‑GPU tasks

Resource usage monitoring

Timeout and exception alerts

Web management panel

The solution fits teams that need to manage a GPU cluster.

GitHub: https://github.com/tiantianGPU/reg-factory<br/>Stars: 300+ | Language: Python | License: MIT
Reg Factory project homepage
Reg Factory project homepage

vLLM Studio – Visual Panel for Large‑Model Deployment

vLLM is one of the most popular inference engines for large models, but its native management UI is minimal. vLLM Studio adds a full‑featured web UI that streamlines deployment, monitoring, and management.

Visual model deployment with point‑and‑click parameter configuration

Real‑time inference performance and GPU usage monitoring

Multi‑model management with one‑click switching

Log viewing and error troubleshooting

pip install vllm-studio vllm-studio serve
GitHub: https://github.com/sybil-solutions/vllm-studio<br/>Stars: 1k+ | Language: Python | License: MIT
vLLM Studio project homepage
vLLM Studio project homepage

All three projects target developer tools: NBD VRAM provides a hardware hack, Reg Factory offers GPU management, and vLLM Studio delivers a deployment panel for large models. Their common goal is to help developers use GPUs more efficiently.

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Model DeploymentvLLMopen-sourceGPUResource SchedulingVRAM
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