Life & fun · December 14, 2022
Software for Remote GPU-over-IP
We built installable software for Windows & Linux that makes any remote Nvidia GPU accessible to, and shareable across, any number of remote clients running local applications, all over standard networking.
Software for Remote GPU-over-IP launched on December 14, 2022 with 138 votes, #264 of 3,688 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 3 years on.
In plain words
This software allows Windows and Linux users to access and share remote Nvidia GPUs across multiple client machines running local applications over standard networks. The installable tool bridges remote graphics processors with local computing environments, enabling distributed GPU resource sharing. It is designed for developers and organizations needing flexible access to GPU computing power without requiring dedicated hardware at each workstation.
written from the facts on this page · September 2026
From the sources
Juice Community Version Public Release. Contribute to Juice-Labs/Juice-Labs development by creating an account on GitHub.
Juice is GPU-over-IP : client/server software that allows GPUs to be used over a standard TCP/IP network. Run the Juice server on a machine with a physical GPU, and then immediately access that GPU from any machine with the Juice client software. Client applications are unaware that the physical GPU is remote and no modifications are necessary to application software . Juice client and server software runs equally well on physical machines , VMs , and containers on both Linux and Windows . The only hard requirements are a GPU to serve and a network connection between the client and server. GPU capacity is increasingly critical to major trends in computing, but its use is hampered by a major…from github.com
Does a similar job
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vGPU and SR-IOV on consumer GPUs2021 · arccompute.com · ▲203Insights on GPU and AI infrastructure from Arc Compute. Read hardware deep-dives, deployment playbooks, and analysis of where the AI compute market is heading.
FFmpeg-over-IP – Connect to remote FFmpeg servers2024 · github.com · ▲147Dear HN, I’m excited to show case a personal project. It has helped me quite a bit with my home lab, I hope it can help you with yours too! ffmpeg-over-ip has two components, a server and a client. You can run the server in an environment with access to a GPU and a locally installed version of ffmpeg, the client only needs network access to the server and no GPU or ffmpeg locally. Both and client and the server need a shared filesystem for this to work (so the server can write output to it, and client can read from it). In my usecase, smb works well if your (GPU) server is a windows machine,…
- GSGpu.st – GPU over SSHJan 2026 · gpu.st · ▲5
Recently I was inspired by exe.dev to finally finish a project I'd been procrastinating on for half a year. You can simply `ssh gpu.st new` and instantly create instances with a variety of GPUs attached. Instances boot a custom image with PyTorch, Jupyter, and the CUDA toolkit installed by default. Currently we give access to 3090s and 4090s for free users; paid users get access to all GPUs.
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