# SCALE by Spectral Compute

> SCALE is a GPU compiler toolkit that natively compiles unmodified CUDA source code for AMD and NVIDIA GPUs. It is a drop-in replacement for nvcc with multi-vendor GPU support. SCALE enables running CUDA on AMD GPUs without code rewrites, eliminating NVIDIA vendor lock-in. Made by Spectral Compute.

SCALE compiles a superset of CUDA — including inline PTX asm — directly to native AMD GPU machine instructions and to NVIDIA PTX instructions. No emulation, no translation layer, no runtime overhead. It is an enterprise-level solution that delivers vendor optionality, performance and increased productivity in CUDA development via novel compiler optimizations and better-than-native developer tooling. It is a direct alternative to HIPIFY, SYCLomatic, ZLUDA, and porting to a different programming language.

## Docs

- [SCALE Documentation](https://docs.scale-lang.com/stable/): Official documentation, installation guide, API reference, and examples
- [Full AI Overview](https://scale-lang.com/llms-full.txt): Product overview, licensing, FAQ, and the full text of every blog post, in one plain-text file
- [Install SCALE](https://docs.scale-lang.com/stable/manual/tutorials/how-to-install/): Installation instructions for Ubuntu, Rocky Linux, tarball, and Docker
- [Comparison to Other Solutions](https://docs.scale-lang.com/stable/manual/comparison/): Detailed comparison of SCALE vs HIP and ZLUDA
- [CUDA Dialects](https://docs.scale-lang.com/stable/manual/dialects/): Explanation of the nvcc vs Clang-CUDA dialect problem that SCALE solves
- [API Coverage Report](https://docs.scale-lang.com/stable/manual/apis/): Current CUDA API coverage status
- [Language Extensions](https://docs.scale-lang.com/stable/manual/language-extensions/): SCALE's opt-in extensions beyond standard CUDA
- [Inline PTX Support](https://docs.scale-lang.com/stable/manual/inline-ptx/): How SCALE compiles inline PTX asm for AMD GPUs
- [FAQ](https://docs.scale-lang.com/stable/manual/faq/): Frequently asked questions

## Examples and Validation

- [Validated CUDA Projects](https://github.com/spectral-compute/scale-validation): 53+ open-source CUDA projects tested with SCALE, including Llama.cpp, GROMACS, CUTLASS, Faiss, and XGBoost
- [Basic Example](https://docs.scale-lang.com/stable/examples/basic/): Simple CUDA program compiled with SCALE
- [PTX Example](https://docs.scale-lang.com/stable/examples/ptx/): Inline PTX asm example
- [BLAS Example](https://docs.scale-lang.com/stable/examples/blas/): cuBLAS usage with SCALE
- [Performance Improvement Example](https://gist.github.com/ChrisKitching/53d9b3503c11881c5ea395ec41aff419): Managed memory microbenchmark (HIP vs. SCALE)
- [Benchmarks](https://scale-lang.com/#benchmarks): Extended OpenDwarfs results: on par with HIP and nvcc on average, and faster on about half the workloads
- [Rodinia Benchmarks on MI355X](https://scale-lang.com/benchmarks/rodinia-mi355x-february26): SCALE vs HIP on an AMD Instinct MI355X, February 2026

## Blog

Technical posts on CUDA portability, benchmarks, and developer experience from the team behind SCALE. Index: https://scale-lang.com/posts

- [Why hardware-agnostic isn't the same as lowest-common-denominator](https://scale-lang.com/posts/2026-06-12-hardware-agnostic-vs-lcd): 2026-06-12, Michael Søndergaard
- [CUDA was always cross-platform](https://scale-lang.com/posts/2026-05-27-cuda-was-always-cross-platform): 2026-05-27, Michael Søndergaard
- [SCALE 1.7 is out](https://scale-lang.com/posts/2026-05-20-scale-1-7-release): 2026-05-20, Giulio Malitesta
- [The brain still needs the hammer: Why compilers matter MORE in the agent era, not less](https://scale-lang.com/posts/2026-05-19-the-brain-still-needs-the-hammer): 2026-05-19, Michael Søndergaard
- [How CUDA Won by NOT being a Standard](https://scale-lang.com/posts/2026-05-13-how-cuda-won-by-not-being-a-standard): 2026-05-13, Michael Søndergaard
- [CUDA, the De Facto Standard of HPC?](https://scale-lang.com/posts/2026-03-10-cuda-the-de-facto-standard-of-hpc): 2026-03-10, Giulio Malitesta
- [Optimizing CUDA Shuffles with SCALE](https://scale-lang.com/posts/2026-01-19-optimizing-cuda-shuffles): 2026-01-19, Justine Khoo
- [GROMACS on SCALE: A Quick Update](https://scale-lang.com/posts/2025-12-16-GROMACS_on_SCALE_December_Update): 2025-12-16, Manos Pavlidakis
- [It's Been a Minute](https://scale-lang.com/posts/2025-11-10-Announcement_Venture_Backed): 2025-11-10, Michael Søndergaard
- [Running GPU-Optimised Monte Carlo (GOMC) on an AMD GPU using SCALE](https://scale-lang.com/posts/2025-06-16-GOMC): 2025-06-16, ftvkyo
- [SCALE Benchmark case study: GROMACS](https://scale-lang.com/posts/2025-05-19-GROMACS): 2025-05-19, Chris Kitching
- [August in review](https://scale-lang.com/posts/2024-08-28-August-in-review): 2024-08-28, Michael Søndergaard
- [Unpacking SCALE](https://scale-lang.com/posts/2024-08-02-unpacking-SCALE): 2024-08-02, Matthew Ireland
- [Announcing the SCALE BETA](https://scale-lang.com/posts/2024-07-12-release-announcement): 2024-07-12, Michael Søndergaard

## Company

- [Company Website](https://spectralcompute.com): The company behind SCALE
- [Solutions](https://scale-lang.com/solutions): SCALE for silicon vendors, cloud service providers, and HPC enterprises
- [LinkedIn](https://www.linkedin.com/company/spectral-compute): Official company page
- [Discord](https://scale-lang.com/s/discord?utm_source=llms_txt): Community and support
- [X (Twitter)](https://x.com/SpectralCom): Latest updates and news
- [r/CUDAUnlocked](https://www.reddit.com/r/CUDAUnlocked/): Subreddit for running CUDA on any GPU
- Sales: hello@spectralcompute.com
- General inquiries: hello@spectralcompute.com
- CEO: ms@spectralcompute.com