Dev tools · alternatives · 2026
24 alternatives to RamShared
Use idle GPU VRAM as safe swap space on Linux & WSL2
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
- 1
Hi everyone, I'm kinda involved in some retrogaming and with some experiments I ran into the following question: "It would be possible to run transformer models bypassing the cpu/ram, connecting the gpu to the nvme?" This is the result of that question itself and some weekend vibecoding (it has the linked library repository in the readme as well), it seems to work, even on consumer gpus, it should work better on professional ones tho
Feb 2026 · github.com · its alternatives →
- 2
cuTile Rust provides a safe, tile-based kernel programming DSL for the Rust programming language. It features a safe host-side API for passing tensors to asynchronously executed kernel functions. - NVlabs/cutile-rs
Jun 2026 · github.com · its alternatives →
- 3
RamDrive that is backed by GPU Memory. Contribute to prsyahmi/GpuRamDrive development by creating an account on GitHub.
2016 · github.com · its alternatives →
- 4
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.
2024 · thundercompute.com · its alternatives →
- 5
I wanted to see how fast an isolated code sandbox could start if I never had to boot a fresh VM. So instead of launching a new microVM per execution, I boot Firecracker once with Python and numpy already loaded, then snapshot the full VM state. Every execution after that creates a new KVM VM backed by a `MAP_PRIVATE` mapping of the snapshot memory, so Linux gives me copy-on-write pages automatically. That means each sandbox starts from an already-running Python process inside a real VM, runs the code, and exits. These are real KVM VMs, not containers: separate guest kernel, separate guest…
Mar 2026 · github.com · its alternatives →
- 6
A "living" Linux process with no memory. Contribute to izabera/zeromaps development by creating an account on GitHub.
2020 · github.com · its alternatives →
- 7
CUDA is NVIDIA's language for GPU programming, allowing you to mix write CPU and GPU code in C++ in one file. By chaining a few projects that compile CUDA to OpenCL, then Vulkan, then WebGPU, you can experiment with this GPGPU language on any hardware.
2025 · hipscript.lights0123.com · its alternatives →
- 8
Computable GPU Index (CGI)free▲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…
Aug 2026 · getcomputable.com · its alternatives →
- 9
Hey HN, I’m Surya and I’m excited to show you WarpBuild! WarpBuild provides fast, secure `x86-64` and `arm64` Github actions runners. This speeds up your workloads by 30%, at half the cost, and takes ~2mins to get started. We’ve been seeing pretty good results since we opened up signups a week ago and I’ve shared some numbers publicly here [1]. Currently, we support linux runners for Github organizations (not personal accounts) and MacOS support is coming soon (~Jan). The way the runners work is deceptively simple: Runners are assigned to hardware that is ideal for build workloads with fast…
2023 · warpbuild.com · its alternatives →
- 10
I built a small Linux tool to deterministically verify GPU PCIe link health and bandwidth. It reports: - Negotiated PCIe generation and width - Peak Host→Device and Device→Host memcpy bandwidth - Sustained PCIe TX/RX utilization via NVML - A rule-based verdict derived from observable hardware data only This exists because PCIe issues (Gen downgrades, reduced lane width, risers, bifurcation) are often invisible at the application layer and can’t be fixed by kernel tuning or async overlap. Linux-only: it relies on sysfs and PCIe AER exposure that Windows does not provide.
Dec 2025 · github.com · its alternatives →
- 11
The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com · its alternatives →
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- 13
Pytorch script hot swap: Change code without unloading your LLM from VRAM - valine/training-hot-swap
2025 · github.com · its alternatives →
- 14
A fast, multi-threaded Redis® and Valkey alternative written in Rust: drop-in compatible, with full-text and vector search built in - kividbio/kividb
3d ago · github.com · its alternatives →
- 15WM
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat · its alternatives →
- 16
Manage your GPUs across NVIDIA, AMD, Intel, and Apple Silicon systems. - treadiehq/gpu-kill
2025 · github.com · its alternatives →
- 17IM
2023 · vram.asmirnov.xyz · its alternatives →
- 18
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.
2022 · github.com · its alternatives →
- 19
I wrote a little LD_PRELOAD library that makes it easy to inspect and interact with a running program's glibc heap. It's fun to pause processes, free a bunch of their allocations, then resume them. Most of the time, the processes continue as though nothing happened, but sometimes they do interesting things :)
2025 · github.com · its alternatives →
- 20
Tabs, splits, and tmux work fine until you have several projects open with logs, tests, and long-running shells. I kept rebuilding context instead of resuming work. Horizon puts shells on an infinite canvas. You can arrange them into workspaces and reopen later with layout, scrollback, and history intact. Built in 3 days with Claude/Codex, dogfooding the workflow as I went. Feedback and contributions welcome.
Mar 2026 · github.com · its alternatives →
- 21
A pipeline that translates Rust GPU code into formal Coq models, as a foundation for memory model proofs - neelsomani/vericuda
2025 · github.com · its alternatives →
- 22PO
Our company Vertex.AI has been working on this for a while but this is the first public release. We're starting with using PlaidML to bring OpenCL support to Keras and more frameworks, platforms, etc are coming. Yes, this means you can use use your AMD GPU for deep learning dev. Sorry, no Mac or Windows support yet although the brave can try building from source (it should work). http://vertex.ai/blog/announcing-plaidml https://github.com/plaidml/plaidml
2017 · its alternatives →
- 23
Hey HN, we’re the developers of OpenLake, an open source storage engine for offloading LLM KV caches from GPU memory into a shared tier of RAM and NVMe. We built OpenLake because KV caches are outgrowing GPU memory. A single 256K token conversation on Gemma 4 31B produces approximately 43GB of KV state, more than half the memory of an 80GB H100. The problem becomes even harder across a cluster: a prefix cached on one GPU host is unavailable when the next request lands on a different GPU, forcing the new GPU to repeat work the fleet has already completed. Once the KV cache is offloaded,…
Jul 2026 · github.com · its alternatives →
- 24
This project contains no code from Linux, BSD, Minix, or any other OS. Everything up until this point is written entirely from scratch, including a pure microkernel (that only implements multiprocessor priority scheduling, memory management, and interprocess communication), a work-in-progress implementation of the standard C library, and a variety of servers that provide drivers and other essential OS functionality. At the time of writing this post, the servers provide drivers for the keyboard, NVMe SSDs (that works on real hardware), a Unix-like virtual file system (with a single root…
2024 · github.com · its alternatives →
Also compare
- Llama 3.1 70B on a single RTX 3090 via NVMe-to-GPU bypassing the CPU alternatives
- cuTile Rust: Safe, data-race-free GPU kernels in Rust alternatives
- RAM Disk Backed by GPU Memory(VRAM) alternatives
- Attaching to a virtual GPU over TCP alternatives
- Sub-millisecond VM sandboxes using CoW memory forking alternatives
- A “living” Linux process with no memory alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →