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  * [ ] SCALE by Spectral Compute SCALE by Spectral Compute Table of
    contents
      + What is SCALE?
      + How does it work?
      + What projects have been tested?
      + Which GPUs are supported?
      + What are the components of SCALE?
      + What are the differences between SCALE and other solutions?
      + Contact us
  * [ ] Getting Started Getting Started
      + Install SCALE
      + Compile CUDA with SCALE
      + [ ] Examples Examples
          o SCALE Example Programs
          o Basic example
          o PTX example
          o BLAS example
  * [ ] Diving deeper Diving deeper
      + Troubleshooting
      + Comparison to other solutions
      + Differences from NVIDIA CUDA
      + Compute Capability Mapping
      + CUDA Dialects
      + [ ] Scale Extensions Scale Extensions
          o API Extensions
          o Language Extensions
  * [ ] Contact Us Contact Us
      + Report a Bug
  * Free Edition License

Table of contents

  * What is SCALE?
  * How does it work?
  * What projects have been tested?
  * Which GPUs are supported?
  * What are the components of SCALE?
  * What are the differences between SCALE and other solutions?
  * Contact us

SCALE by Spectral Compute#

What is SCALE?#

SCALE is a GPGPU programming toolkit that allows CUDA applications to
be natively compiled for AMD GPUs.

SCALE does not require the CUDA program or its build system to be
modified.

Support for more GPU vendors and CUDA APIs is in development.

To get started:

  * See the tutorial.
  * Review the examples.
  * Contact us for help.

How does it work?#

SCALE has several key innovations compared to other cross-platform
GPGPU solutions:

  * SCALE accepts CUDA programs as-is. No need to port them to
    another language. This is true even if your program uses inline
    PTX asm.
  * The SCALE compiler accepts the same command-line options and CUDA
    dialect as nvcc, serving as a drop-in replacement.
  * "Impersonates" an installation of the NVIDIA CUDA Toolkit, so
    existing build tools and scripts like cmake just work.

What projects have been tested?#

We validate SCALE by compiling open-source CUDA projects and running
their tests. The following open-source projects are currently part of
our nightly automated tests and pass fully:

  * NVIDIA Thrust
  * Blender Cycles
  * AMGX
  * llama-cpp
  * faiss
  * xgboost
  * GOMC
  * stdgpu
  * hashcat

Which GPUs are supported?#

The following GPU targets are supported, and are covered by our
nightly tests:

  * AMD gfx1030 (Navi 21, RDNA 2.0)
  * AMD gfx1100 (Navi 31, RDNA 3.0)

The following GPU targets have undergone ad-hoc manual testing and
"seem to work":

  * AMD gfx1010
  * AMD gfx1101

We are working on supporting the following GPUs:

  * AMD gfx900 (Vega 10, GCN 5.0)

Contact us if you want us to expedite support for a particular AMD
GPU architecture.

What are the components of SCALE?#

SCALE consists of:

  * An nvcc-compatible compiler capable of compiling nvcc-dialect
    CUDA for AMD GPUs, including PTX asm.
  * Implementations of the CUDA runtime and driver APIs for AMD GPUs.
  * Open-source wrapper libraries providing the "CUDA-X" APIs by
    delegating to the corresponding ROCm libraries. This is how
    libraries such as cuBLAS and cuSOLVER are handled.

What are the differences between SCALE and other solutions?#

Instead of providing a new way to write GPGPU software, SCALE allows
programs written using the widely-popular CUDA language to be
directly compiled for AMD GPUs.

SCALE aims to be fully compatible with NVIDIA CUDA. We believe that
users should not have to maintain multiple codebases or compromise on
performance to support multiple GPU vendors.

SCALE's language is a superset of NVIDIA CUDA, offering some opt-in
language extensions that can make writing GPU code easier and more
efficient for users who wish to move away from nvcc.

SCALE is a work in progress. If there is a missing API that is
blocking your attempt to use SCALE, please contact us so we can
prioritise its development.

Contact us#

There are multiple ways to get in touch with us:

  * Join our Discord
  * Send us an e-mail at [email protected]

 
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