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Intel_XPU.md

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GSPLAT on Intel GPUs

gsplat supports creation and rendering on Intel GPUs through the SYCL kernel backend. This provides support for both integrated (Alder Lake Arc and onward) and discrete GPUs (Arc Alchemist and newer, such as the A770 and B580).

Supported Features:

  • 3DGS fused training
  • 3DGS packed representation
  • Distributed training (PyTorch 2.8+)
  • MCMC strategy (relocation kernel)
  • 2DGS fused training
  • 2DGS packed representation
  • 3DGUT kernels (+FTheta cameras)
  • Fused Bilateral grid kernels (from https://github.com/harry7557558/fused-bilagrid)
  • 3DGS Compression (requires PLAS)
  • rasterize_to_indices_{2,3}dgs and rasterize_to_pixels_from_world_3dgs kernels (only used internally for testing)

The kernels are optimized and use mixed precision (some data is represented as half), so the results differ slightly from the CUDA kernel results.

Installing (Linux or Windows):

  • PyTorch XPU: Install the PyTorch XPU version.

    pip install torch torchvision --index-url https://download.pytorch.org/whl/xpu

    Next install gsplat-xpu directly from here (for PyTorch 2.10+xpu). Otherwise, you can build and install from source.

    pip install gsplat --find-links https://isl-org.github.io/gsplat/whl/gsplat

  • Intel oneAPI Toolkit: Ensure you have the Intel oneAPI Toolkit installed. This provides the necessary compilers and libraries for SYCL development.

    Note: The OneAPI toolkit version must match the version used to build PyTorch XPU. Check the PyTorch XPU OneAPI version with:

    pip show intel-cmplr-lib-ur   # dependency of torch-xpu
# ...
# Version: 2025.3.1
# ...

  • Configure your build environment:

    In Linux:

    source /opt/intel/oneapi/setvars.sh

    Or in Windows, setup your Visual Studio build environment and then OneAPI build environment. For example:

    cmd /k "C:\Program Files (x86)\Intel\oneAPI\setvars.bat"
powershell
$env:DISTUTILS_USE_SDK=1

  • Finally, build and install the project's Python extension.

    pip install --extra-index-url=https://download.pytorch.org/whl/xpu .

    Alternately, you can build a wheel for distribution with:

    PIP_EXTRA_INDEX_URL=https://download.pytorch.org/whl/xpu python -m build --no-isolation --wheel .

Evaluation

We evaluate gsplat-xpu on the Mip-NeRF 360 dataset and measure PSNR, SSIM, LPIPS and the number of Gaussians used. We also measure the memory used and the run time on an Intel Arc B580 dGPU and an Intel Arc B390 iGPU. To run the evaluation yourself, download the MIPS-NeRF 360 dataset and install other requirements:

```bash
cd examples
pip install --extra-index-url=https://download.pytorch.org/whl/xpu -r requirements_xpu.txt
# download mipnerf_360 benchmark data
python datasets/download_dataset.py
```

The last command will also build and install the fused-ssim package. Before running benchmarks, you can add --max-steps 7000 to each simple_trainer.py command in benchmarks/basic{,_2dgs}.sh, if you have limited memory, or want to run the training faster. Run the benchmarks with:

```bash
# run batch evaluation
bash benchmarks/basic.sh
bash benchmarks/basic_2dgs.sh
```

Arc B580 dGPU

3DGS Reproduced metrics

PSNR Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 24.01 29.66 27.26 26.59 28.65 28.70 26.03
30k steps 1 31.89 29.14 1 30.90 31.06 1
SSIM Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 0.6808 0.9262 0.8865 0.8370 0.9047 0.8945 0.7378
30k steps 1 0.9446 0.9158 1 0.9318 0.9239 1
LPIPS Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 0.2997 0.1462 0.1929 0.1195 0.1220 0.2136 0.2339
30k steps 1 0.1179 0.1414 1 0.08607 0.1520 1
Num GSs Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 3.95 M 1.19 M 1.06 M 4.20 M 1.77 M 1.14 M 4.04 M
30k steps 1 1.28 M 1.27 M 1 1.90 M 1.63 M 1

3DGS Training time and memory

Mip-NeRF 360 scene Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps Mem (GB) 5.846 2.009 1.730 6.177 2.737 1.861 5.921
30k steps Mem (GB) 1 2.043 1.986 1 2.923 2.463 1
7k steps time (s) 588.5 534.4 625.3 793.6 919.1 645.1 519.3
30k steps time (s) 1 2612 3520 1 5027 3317 1

2DGS Reproduced metrics

PSNR Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 23.59 29.73 27.25 26.31 29.02 29.56 25.69
30k steps 25.33 32.13 28.90 27.39 31.33 31.43 26.72
SSIM Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 0.6578 0.9277 0.8819 0.8222 0.9021 0.9026 0.7225
30k steps 0.7570 0.9453 0.9097 0.8567 0.9283 0.9249 0.7743
LPIPS Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 0.3091 0.1441 0.1935 0.1289 0.1231 0.1988 0.2403
30k steps 0.1745 0.1173 0.1503 0.08466 0.09162 0.1555 0.1565
Num GSs Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps 2.52 M 0.911 M 0.695 M 2.18 M 0.856 M 0.839 M 2.69 M
30k steps 3.67 M 0.929 M 0.731 M 2.39 M 0.870 M 1.03 M 3.30 M

2DGS Training time and memory

Mip-NeRF 360 scene Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps Mem (GB) 4.621 2.129 1.832 4.004 2.063 2.057 4.766
30k steps Mem (GB) 6.491 2.129 1.854 4.278 2.063 2.224 5.802
7k steps time (s) 560.0 758.2 666.3 609.3 732.8 643.8 545.6
30k steps time (s) 3483 3308 2941 3101 3196 2936 3117

Arc B390 iGPU

3DGS Reproduced metrics

7k steps Bicycle Bonsai Counter Garden Kitchen Room Stump
PSNR 24.02 29.72 27.40 26.61 29.24 29.56 25.31
SSIM 0.6513 0.9252 0.8914 0.8369 0.9173 0.9039 0.6955
LPIPS 0.3558 0.1525 0.1891 0.1198 0.1102 0.2037 0.2941
Num GSs 3.28 M 0.99 M 0.74 M 4.17 M 1.07 M 0.80 M 4.01 M

3DGS Training time and memory

Mip-NeRF 360 scene Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps Mem (GB) 5.016 1.642 1.264 6.142 1.678 1.366 5.932
7k steps time (s) 1346.5 1124.1 1231.0 1958.6 1496.2 983.1 1215.6

2DGS Reproduced metrics

7k steps Bicycle Bonsai Counter Garden Kitchen Room Stump
PSNR 23.92 29.88 27.38 25.95 29.37 29.98 25.13
SSIM 0.6418 0.9301 0.8897 0.7992 0.9128 0.9086 0.6855
LPIPS 0.3443 0.1446 0.1843 0.1520 0.1123 0.1919 0.2902
Num GSs 2.13 M 0.79 M 0.56 M 1.66 M 0.72 M 0.62 M 2.40 M

2DGS Training time and memory

Mip-NeRF 360 scene Bicycle Bonsai Counter Garden Kitchen Room Stump
7k steps Mem (GB) 3.026 1.9185 1.5837 3.026 1.8087 1.6828 4.263
7k steps time (s) 1502.5 1868.3 2121.1 1502.5 1816.6 1591.3 1409.4

Footnotes

  1. Out of memory. ↩ ↩2 ↩3 ↩4 ↩5 ↩6 ↩7 ↩8 ↩9 ↩10 ↩11 ↩12 ↩13 ↩14 ↩15 ↩16 ↩17 ↩18