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b99c510 ebf0ed9 b99c510 ebf0ed9 b99c510 ebf0ed9 b99c510 ebf0ed9 b99c510 ebf0ed9 b99c510 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | # ExecuTorch Wasm + WebGPU runtime
`executorch_wasm_lib.js` and `executorch_wasm_lib.wasm` are the ExecuTorch Wasm
bindings (`extension/wasm`) with the WebGPU backend, linked into one web bundle.
The `.js` loader ships in this folder. The `.wasm` is hosted on Hugging Face
(`executorch-community/ExecuTorch-WebGPU-Runtime`, pinned in `src/config/runtime.js`),
downloaded and checked against the sha256 below like a model file.
Every demo in the playground shares this one runtime (`src/runtime/executorch.js`).
The JS file defines `createExecuTorch()`. After `await et.initWebGPU()`, a `.pte`
loads with `et.Module.load(path)` and `loadMethod('forward')`, and runs with an
async `forward([tensors])`.
## Source
Built from the ExecuTorch source tree of 2026-10-16 (`version.txt` 1.6.0) with the two
changes that make WebGPU run in the Wasm build, both merged upstream:
1. pytorch/executorch#23938: the `EXECUTORCH_BUILD_WASM_WEBGPU` option, which links the
WebGPU backend into `extension/wasm`, and the `initWebGPU()` binding.
2. pytorch/executorch#23914: `WebGPUGraph::propagate_resize` resizes every operand before
its consumer in one pass, so a multi-token LLM prefill works.
A build from ExecuTorch main that contains both, with the commands below, should give the
same files. The emdawnwebgpu override (`EXECUTORCH_WEBGPU_EMDAWNWEBGPU_PORT`) was only
needed because the build machine could not reach GitHub; without it, Emscripten downloads
the same emdawnwebgpu version itself.
## Toolchain
- Emscripten 4.0.19, official release build `8b01e2ec3f33e6b94842096d7312ce4ef5f33f6c`.
- emdawnwebgpu v20251002.162335, the version Emscripten 4.0.19 pins. It was rebuilt
from Dawn source at `01940842b667a7812d0e4ca0ef4367fbec294241`, using Dawn's
own packaging recipe.
- CMake 3.31, Ninja 1.13. The configure step needs a Python with `torch`
(for `torchgen`).
## Build
A small consumer project links the bindings into a distributable bundle, as
described under "Building for Web" in `extension/wasm/README.md`:
```cmake
cmake_minimum_required(VERSION 3.29)
project(executorch_web)
add_subdirectory(${ET_SRC} executorch)
add_executable(executorch_wasm_lib)
target_link_libraries(executorch_wasm_lib PRIVATE executorch_wasm)
target_link_options(executorch_wasm_lib PRIVATE
-sMODULARIZE=1 -sEXPORT_NAME=createExecuTorch -sENVIRONMENT=web,worker
-sFORCE_FILESYSTEM=1 -sEXPORTED_RUNTIME_METHODS=FS -sINITIAL_MEMORY=64MB
-sEXPORT_EXCEPTION_HANDLING_HELPERS=1)
```
```bash
emcmake cmake -S <consumer project> -B build -G Ninja -DCMAKE_BUILD_TYPE=Release \
-DET_SRC=<executorch> \
-DEXECUTORCH_BUILD_WASM=ON -DEXECUTORCH_BUILD_WEBGPU=ON -DEXECUTORCH_BUILD_WASM_WEBGPU=ON \
-DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON -DEXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR=ON \
-DEXECUTORCH_BUILD_EXTENSION_MODULE=ON -DEXECUTORCH_BUILD_EXTENSION_NAMED_DATA_MAP=ON \
-DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
-DEXECUTORCH_ENABLE_LOGGING=ON -DEXECUTORCH_LOG_LEVEL=Info \
-DEXECUTORCH_WEBGPU_EMDAWNWEBGPU_PORT=<emdawnwebgpu_pkg>/emdawnwebgpu.port.py \
"-DCMAKE_C_FLAGS=-ffile-prefix-map=<executorch>=executorch" \
"-DCMAKE_CXX_FLAGS=-ffile-prefix-map=<executorch>=executorch" \
-DPYTHON_EXECUTABLE=<python with torch>
cmake --build build --target executorch_wasm_lib
```
The WebGPU Wasm option itself adds `-sASYNCIFY -sASYNCIFY_STACK_SIZE=65536
-sALLOW_MEMORY_GROWTH=1 -sMAXIMUM_MEMORY=4GB -fexceptions`. The full portable
kernel library is linked (no selective build). Logging is at Info, so a failed
load or run prints the reason to the console. `-ffile-prefix-map` keeps
build-machine paths out of the binary.
## Files
| File | Bytes | sha256 |
|---|---:|---|
| `executorch_wasm_lib.js` | 165,877 | `8a631b1537927f8f2ef184d9f1b343061f47df0a32ddb8f5190d74e80d40618e` |
| `executorch_wasm_lib.wasm` | 6,562,188 | `35a9087d0b6cd86c279e7111adfd54a58156bd993928b20f63348f1043652eb4` |
## Checked with this build
Headless Chromium 141, WebGPU on SwiftShader (no `shader-f16`), with the
playground's models compared against ExecuTorch CPU references:
- Depth Anything V2 Small, MODNet, Real-ESRGAN, D-FINE S: max abs difference
between 0 and 4.6e-3.
- SAM 2.1 Hiera Tiny: mask IoU 1.000 on a click, a second click, and a box prompt.
The playground's own end-to-end checks, through the real UI, cover Qwen3 0.6B,
Llama 3.2 1B, SAM 2.1, Depth Anything V2, D-FINE S and Whisper base. Real GPUs
and the `shader-f16` kernel paths have not been tested with this build.
|