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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.
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- 50 reach 5 · trust 5 · quality 25 · freshness 15
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- llms.txt
- https://scale-lang.com/llms.txt
- llms-full.txt
- https://scale-lang.com/llms-full.txt
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- 36
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- 5737 bytes
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- #935862
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- Developer tools
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- Documentation: developer or product docs worth reading, nothing to call
- First seen
- 2026-10-25T18:10:30.576Z
- Last checked
- 2026-10-26T09:07:15.213Z
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Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-26T09:07:13.593Z. Cached copy · Source on scale-lang.com
# 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
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| Domain | Title | Category | Country | Authority | llms.txt | llms-full.txt | Save |
|---|---|---|---|---|---|---|---|
| amd.com | ROCm documentation | documentation Developer tools Documentation and reference | — | 68 | ✓ | ✓ | |
| massedcompute.com | Massed Compute: On\-demand GPUs, bare metal, and clusters built for real AI workloads\. | interface AI and machine learning Infrastructure | — | 54 | ✓ | ||
| modular.com | Modular | interface AI and machine learning Infrastructure | US | 60 | ✓ | ||
| cirrascale.com | Cirrascale Cloud Services | transactional Infrastructure AI and machine learning | US | 52 | ✓ | ||
| thundercompute.com | Thunder Compute (https://www.thundercompute.com) | interface Infrastructure AI and machine learning | — | 55 | ✓ | ||
| nvidia.com | NVIDIA Corporation | documentation AI and machine learning Developer tools +1 | US | 71 | ✓ | ||
| crusoe.ai | Crusoe Cloud Documentation | transactional Industry and manufacturing Infrastructure +2 | US | 59 | ✓ | ||
| canirun.ai | CanIRun.ai | documentation AI and machine learning | — | 52 | ✓ |
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