Attaching to a virtual GPU over TCP
We developed a tool to trick your computer into thinking it’s attached to a GPU which actually sits across a network. This allows you to switch the number or type of GPUs you’re using with a single command.
Attaching to a virtual GPU over TCP launched on August 9, 2024 with 344 votes, #125 of 5,471 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
This tool allows computers to connect to graphics processing units located on remote servers over a network connection, presenting them as locally attached hardware. Users can dynamically switch between different GPU types and quantities through simple commands without physical reconfiguration. It is designed for organizations and developers who need flexible GPU resources and want to manage their computing infrastructure more efficiently.
written from the facts on this page · September 2026
From the sources
Thunder Compute makes GPUs abundant with GPU virtualization research, cloud infrastructure, and enterprise partnerships that unlock more data center capacity.
Every scarce resource in computing becomes abundant. CPUs, storage, networking, and memory all made this transition, GPUs have not. For GPUs, abundance will come not only from building more chips, but from using software to make better use of the chips already deployed. Today, GPUs remain underutilized. The best solutions sit at the workload layer, batching inference requests or queueing training jobs across fleets of servers. Meanwhile, the systems layer remains largely untouched. Virtualization is now universal for CPUs, storage, networking, and memory, but does not yet exist for GPUs. Thunder Compute exists to fill this gap. We are a systems lab with commercial focus, productionizing…from thundercompute.com
Does a similar job
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Software for Remote GPU-over-IP2022 · github.com · ▲138We 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.
Computable GPU Index (CGI)Aug 2026 · getcomputable.com · ▲444Hey we are Computable. We spent years building trading infrastructure at Jump Trading and Coinbase. From that point of view, compute looks like energy markets before 2000: everything trades through private bilateral leases, there’s no visible price, and nothing can be resold. The same H100 rents at a 2x spread depending on who’s asking, and once you sign a 24-month lease, it can never change hands. So we built a market for GPU nodes, sold by the calendar week. Here are three things you can do on it that you can’t do anywhere else: - Buy exactly the weeks you need. Three nodes for the last…
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.
- GCgpudeploy.com – "Airbnb" for GPUs2024 · gpudeploy.com · ▲267
Hi HN, YC w24 company here. We just pivoted from drone delivery to build gpudeploy.com, a website that routes on-demand traffic for GPU instances to idle compute resources. The experience is similar to lambda labs, which we’ve really enjoyed for training our robotics models, but their GPUs are never available for on-demand. We are also trying to make it more no-nonsense (no hidden fees, no H100 behind “contact sales”, etc.). The tech to make this work is actually kind of nifty, we may do an in-depth HN post on that soon. Right now, we have H100s, a few RTX 4090s and a GTX 1080 Ti online.…
GPU Terminal by Context.dev5d ago · gpu.context.dev · ▲109Compare GPU rental prices across cloud providers
Rgpu – a PyTorch device whose tensors live on a remote GPU14d ago · github.com · ▲57Keep Python on your laptop. Run PyTorch operations and hold tensors on a remote GPU, including from a Mac with no CUDA installation. - ymcrcat/rgpu
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