Alternatives
Products that do what Compute.cx is simple (modal.com like) interface for on-demand GPUs does
Hi everyone, Please checkout compute.cx which is a simple cli interface for using on demand GPUs from RunPod and HotAisle. I created this because I really like the ease of modal.com for severless gpu access, but don’t always want to pay their markup. Compute.cx gives the same DX but on public on-demand GPUs like runpod and hotaisie. Please try it out, and write to me [email protected] for any questions/suggestions, or file a bug report on https://github.com/theoriclabs/docs.compute.cx Thanks! Harsh Gupta https://x.com/hargup13 P.S. BYOK AWS, GCP and…
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Hey 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…
Jul 2026 · getcomputable.com
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2017 · github.com
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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
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2019 · dev.to
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It's a chrome extension that automatically loads the specs from the Hugging Face model card into the calculation. > To test it, install the extension (no registration/key needed) and navigate to a HF model page. Then click the "VRAM" icon on the top right to open the sidepanel. You can specify quantization, batch size, sequence length, etc. Works for inference & fine-tuning. If it does not fit on the specified GPUs, it gives you an advise on how to still run it (e.g. lowering precision). It is inspired at my work, where we were constantly exporting metrics from HF to estimate required…
2025 · chromewebstore.google.com
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We'd like to introduce HN to Spell, which is a tool for easily running ML/DL jobs remotely. As Deep Learning has grown we see engineers and researchers struggle to incorporate running on GPUs into their workflow. So we built Spell to be the easiest way to get code running elsewhere - like the bash '&' operator but for remote machines. Sign up for an account at https://web.spell.run/waitlist, which includes $300 in credits for GPU time. There's a waitlist, but we'll be approving accounts as they come in. Here are some of the features we really wanted and built into Spell:…
2018
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Artifex is a machine-first, headless CLI runtime built for autonomous coding agents to author, validate, and render media node graphs locally. The agent talks to Artifex through a structured CLI interface. Workflows are DAGs, and each node is a plugin that can implement its own execution logic.. Each node has capability to inject logic into graph processing, WebGPU rendering, audio processing and their own SKILL.md file. Nodes can also inject their react components (not available with CLI) - which will be available with the desktop app. Execution is topological and supports checkpoint…
23d ago · gatewai.studio
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Hi HN! I've been hacking on this side project for the last month or two with the goal of making it dead simple to use cloud GPUs. I ran into this problem personally during the phd, and built my own tooling around it. I always thought it'd be fun to try to turn that tooling into a more general product... and bitbop.io is the result! All you have to do is run `ssh bitbop.io`, and you get your own personal dev GPU workstation in the cloud. Looking forward to hearing your thoughts!
2024 · twitter.com
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I've been recently working on porting standard C library functions to work on the GPU https://libc.llvm.org/gpu/. A colleague of mine suggested using it to run DOOM, so that's what I did. It runs on both AMD and NVIDIA GPUs and it is completely playable. This works by targeting C code directly for the GPU via cross-compilation in clang, looks something like this https://godbolt.org/z/hh44a6vKr. The LLVM C library will provide the headers, C library functions, and the kernel that calls the main function, so we only need to compile the DOOM source code…
2024 · github.com
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You know that old TI calculator you used in high school, then put in a box and forgot about? Have you ever wished you had an operating system for your calculator with preemptive multitasking, dynamic memory management, a tree filesystem conforming to the FHS, and all the comforts of Unix? Well, good news: that's totally a thing that exists. I've been working on my kernel for about three and a half years now and I'm looking for new contributors to help out. It's written entirely in z80 assembly, and it's both challenging and fun to work on. There's an IRC channel for contributors or people…
2014
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I've made a GPU comparison site: https://gpu-prices.com/US/ Yes, there was one yesterday - I got beaten to it. This one is different in that I've put a lot of work into categorisation, so you can filter down quite precisely. For example, VRAM-per-dollar, limiting to Nvidia, and a minimum performance score allow you to find good ML GPUs. It currently supports Australia, Canada, Ireland, the UK, and the US. The tech stack is Python for data pull and static site generation then Cloudflare Pages for actually serving the site. It updates three times a day, but I could increase…
2024 · gpu-prices.com
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Hey HN, I wrote a compute shader emulator that started as a 50-line script to help me understand reduction shaders. What makes this implementation interesting is its technical approach; I've leveraged Nim's macros and closure iterators to simulate lockstep execution of logical threads. The emulator runs GPU compute shaders on CPU, simulating workgroups and subgroups with proper synchronization. It supports GLSL subgroup operations and provides nice debugging messages. The emulator works with Nim code that follows compute shader patterns I've documented some technical aspects here:…
2025 · github.com
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After the incredible response to our launch of the first online CUDA playground, we have just shipped something we think all you GPU programming and ML enthusiasts will love. Introducing LeetGPU Challenges--the place to compete on writing the fastest CUDA kernels. We have problems like matrix multiplication, agent simulation, multi-head self-attention, with more dropping every couple of days! We have a lot of really cool things coming up, including support for PyTorch, TensorFlow, JAX, TinyGrad; Multi-GPU programs; H100, V100, A100 GPU options Give it a try and let us know what you think!
2025 · leetgpu.com
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After 1 year & 3 months of work, HCC the C -> SPIR-V compiler for Vulkan has its first release!!! - vertex, pixel & compute shaders - share structs, functions & enums across the CPU & GPU - fully bindless resources - multiple shaders in a single file - vulkan 1.3 + - windows & linux support - aims for C11 support - textures, atomics, quad & wave intrinsics - scalars, vectors, matrices maths library - samples app with 5 shader samples - playground app (shadertoy clone)
2023 · github.com
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