Spectral Compute

Book a slot with Michael → calendar.app.google/9siyiNivMTj1gn… Learn how SCALE is bringing vendor optionality to the CUDA ecosystem - no rewrites needed. Event details: luma.com/g03nmrq8

Our CEO @SpectralMichael will be a keynote speaker at the Beyond Summit 2026 on April 8 in San Francisco, joining a panel of leading voices from HPC and AI infrastructure. Hosted by @TensorWave 👇

And your engineers get better tools in the process: clangd IDE integration, modern compiler diagnostics, and compiler optimizations that get the most out of the latest silicon - while keeping vendor-deprecated GPUs productive. Visit scale-lang.com and join our Discord server to learn more: discord.com/invite/KNpgGbT…

SCALE eliminates the Talent Tax. Your unmodified CUDA code compiles natively for both NVIDIA and AMD GPUs. Same codebase. Same engineers. No rewrites.

The real lock-in is the people. 5M+ developers write CUDA code. Two decades of expertise, baked into every team, hiring pipeline, and CS curriculum. Every "CUDA alternative" asks you to throw that away. That's the Talent Tax.

Next week, @SpectralMichael is at @TensorWave’s Beyond Summit in SF discussing SCALE: native compilation of your CUDA codebases for NVIDIA & AMD GPUs. No translation layers. See you there! luma.com/g03nmrq8

Want to talk with the developers behind SCALE? Join our Discord server: discord.com/invite/KNpgGbT…

If your code works in CUDA, it compiles in SCALE. No ports, no translation layers, no vendor lock-in. Read the docs and see the full target list here: docs.scale-lang.com/stable/

The industry spends a lot of time arguing about the newest GPUs. We just make sure your CUDA code runs on all of them. 🧵

Check out the cryptic nvcc errors we gathered, grab the VSCode integration tutorial, and join the compiler engineers in our Discord. Links here 👇 • scale-lang.com • docs.scale-lang.com/stable/manual/… • discord.com/invite/KNpgGbT…

You can keep serving the clients who demand NVIDIA. But when you’re ready to seamlessly shift to a hybrid GPU provisioning approach and drastically lower your infra TCO, you won't have to rewrite a single line of code. Neither will your clients.

Come for the modern CUDA tooling. Stay for the hardware freedom. If you've ever been stumped by a cryptic nvcc error, we feel you. When you write CUDA code, you usually lose out on standard C++ features like reliable autocompletion and precise diagnostics.

If you're at the event and want to talk better CUDA tooling or how to actually escape vendor lock-in, 𝘴𝘦𝘯𝘥 𝘶𝘴 𝘢 𝘋𝘔 𝘵𝘰 𝘤𝘰𝘯𝘯𝘦𝘤𝘵.

It fixes your current workflow headaches, and simultaneously unlocks the ability to 𝗰𝗼𝗺𝗽𝗶𝗹𝗲 𝘆𝗼𝘂𝗿 𝗖𝗨𝗗𝗔 𝗰𝗼𝗱𝗲 𝗳𝗼𝗿 𝗯𝗼𝘁𝗵 𝗡𝗩𝗜𝗗𝗜𝗔 𝗮𝗻𝗱 𝗔𝗠𝗗 𝗵𝗮𝗿𝗱𝘄𝗮𝗿𝗲.

We're on the ground at @cloudfest in Europa-Park this week! We’re spending the next few days talking to infrastructure teams about a practical path to 𝘩𝘺𝘣𝘳𝘪𝘥 𝘎𝘗𝘜 𝘱𝘳𝘰𝘷𝘪𝘴𝘪𝘰𝘯𝘪𝘯𝘨.