Webgpu Local Testing

Running ONNX Runtime WebGPU Tests Locally on Linux (No GPU)

Reusable knowledge for exercising the WebGPU execution provider on a Linux box

with no physical GPU.

> Scope: Linux ORT WebGPU only. macOS uses the Metal backend and a real GPU;

> this skill is the off-Mac story for running WebGPU EP kernels in CI-less dev loops.

1. Why software Vulkan is enough

On Linux, ORT's WebGPU EP runs on Dawn with the Vulkan backend. Vulkan does

not require a hardware GPU — Mesa lavapipe is a software (CPU) Vulkan adapter that

Dawn enumerates like any other device. For EP correctness tests this is sufficient

because:

• Many host-side validation paths (shape/broadcast checks, ORT_ENFORCEs) fire

before any shader is dispatched. E.g. the WebGPU broadcast ORT_ENFORCE runs

host-side, so the failure is observable on a software adapter without ever touching

the GPU.

• Element-wise and broadcasting kernels that do dispatch run correctly (if slowly) on

lavapipe, so their numeric output can be validated against the CPU reference.

You are trading speed for not needing hardware. It is not a substitute for a real

GPU on perf-sensitive or driver-specific paths — but for kernel correctness it is the

practical local loop.

> Scope — what lavapipe can and cannot validate. Software Vulkan covers (a)

> host-side failures (shape/broadcast ORT_ENFORCEs that fire *before* any shader

> dispatch) and (b) MatMul-free kernels that dispatch. It does NOT cover any

> graph that contains a MatMul — the MatMul family crashes lavapipe's LLVM JIT (see

> §5). This explicitly includes the motivating expanded-Attention node tests

> (test_attention_4d_softcap_neginf_mask_expanded): they decompose to

> softmax(Q·Kᵀ + bias)·V, which contains MatMuls, so they **cannot run on

> lavapipe. For those, macOS-arm64 Metal is the source of truth**. Concretely, the

> #28969 WebGPU broadcast-underflow fix was validated on lavapipe via a standalone

> Add-broadcast OpTester proxy (a host-side enforce/shape path) — NOT via the

> expanded-Attention node test. Never run lavapipe green and conclude an

> Attention/MatMul fix is validated off-Mac.

2. Install the software Vulkan stack (Azure Linux — use dnf, NOT apt)

dnf install -y mesa-vulkan-drivers vulkan-loader
# optional, for sanity-checking the adapter:
dnf install -y vulkan-tools && vulkaninfo | head

mesa-vulkan-drivers provides lavapipe; vulkan-loader provides the ICD loader.

The lavapipe ICD manifest lands at /usr/share/vulkan/icd.d/lvp_icd.<arch>.json —

lvp_icd.x86_64.json on x86_64, lvp_icd.aarch64.json on arm64. The examples below

use the x86_64 name; substitute your arch, or glob it:

VK_ICD_FILENAMES=$(echo /usr/share/vulkan/icd.d/lvp_icd.*.json).

3. Build with --use_webgpu

./build.sh --config Release --parallel --use_webgpu

See the ort-build skill for general build phases and flags.

4. Run the WebGPU provider tests

WebGPU operator/kernel tests are provider op tests — they build into the

onnxruntime_provider_test target (NOT onnxruntime_test_all; see the ort-test

skill for the executable taxonomy). Point the Vulkan loader at the lavapipe ICD and

select a subset with --gtest_filter:

cd build/Linux/Release
VK_ICD_FILENAMES=/usr/share/vulkan/icd.d/lvp_icd.x86_64.json \
  ./onnxruntime_provider_test --gtest_filter="*WebGPU*"

VK_ICD_FILENAMES forces Vulkan to load only lavapipe, so the run is

deterministic regardless of what else is installed.

5. Gotcha: lavapipe crashes on the MatMul family

MathOpTest.MatMulFloatType (and other MatMul-family tests) crash lavapipe with:

LLVM ERROR: Instruction Combining did not reach a fixpoint after 1 iterations

This is a pre-existing limitation of software Vulkan (Mesa lavapipe's LLVM JIT),

not an ORT bug. Exclude the MatMul family from broad lavapipe runs:

VK_ICD_FILENAMES=/usr/share/vulkan/icd.d/lvp_icd.x86_64.json \
  ./onnxruntime_provider_test --gtest_filter="*WebGPU*:-*MatMul*"

6. Why this matters: the Linux webgpu CI leg is build-only

The Linux webgpu CI leg (py-linux-webgpu-stage.yml) only builds — it does not run

WebGPU kernels. A green Linux webgpu leg therefore does not mean any WebGPU test

actually executed. The macOS-arm64 webgpu leg is the only CI leg that runs WebGPU

backend node tests. So a local lavapipe run is the practical way to **actually exercise

WebGPU kernels off-Mac** before you push.

But mind the §1 scope: lavapipe covers host-side enforce/shape paths and MatMul-free

kernels only. Any MatMul-containing graph — including the expanded-Attention node

tests (test_attention_4d_softcap_neginf_mask_expanded) — crashes lavapipe and runs

only on the macOS-arm64 Metal leg, which is the source of truth for those. A green

lavapipe run never validates a MatMul/Attention fix off-Mac.