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ggml: WebGPU disable SET_ROWS for now (#15078)

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* Add paramater buffer pool, batching of submissions, refactor command building/submission

* Add header for linux builds

* Free staged parameter buffers at once

* Format with clang-format

* Fix thread-safe implementation

* Use device implicit synchronization

* Update workflow to use custom release

* Remove testing branch workflow

* Disable set_rows until it's implemented

* Fix potential issue around empty queue submission

* Try synchronous submission

* Try waiting on all futures explicitly

* Add debug

* Add more debug messages

* Work on getting ssh access for debugging

* Debug on failure

* Disable other tests

* Remove extra if

* Try more locking

* maybe passes?

* test

* Some cleanups

* Restore build file

* Remove extra testing branch ci
This commit is contained in:
Reese Levine
2025-08-05 16:26:38 -07:00
committed by GitHub
parent fd1234cb46
commit 9515c6131a
2 changed files with 48 additions and 26 deletions
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2
.github/workflows/build.yml vendored
View File

@@ -179,6 +179,7 @@ jobs:
- name: Test - name: Test
id: cmake_test id: cmake_test
run: | run: |
export LLAMA_SET_ROWS=0
cd build cd build
ctest -L main --verbose --timeout 900 ctest -L main --verbose --timeout 900
@@ -437,6 +438,7 @@ jobs:
- name: Test - name: Test
id: cmake_test id: cmake_test
run: | run: |
export LLAMA_SET_ROWS=0
cd build cd build
# This is using llvmpipe and runs slower than other backends # This is using llvmpipe and runs slower than other backends
ctest -L main --verbose --timeout 3600 ctest -L main --verbose --timeout 3600

72
ggml/src/ggml-webgpu/ggml-webgpu.cpp
View File

@@ -118,8 +118,6 @@ struct webgpu_context_struct {
wgpu::Limits limits; wgpu::Limits limits;
std::recursive_mutex mutex; std::recursive_mutex mutex;
std::mutex get_tensor_mutex;
std::mutex init_mutex;
bool device_init = false; bool device_init = false;
@@ -139,6 +137,8 @@ struct webgpu_context_struct {
// Parameter buffers associated with the staged command buffers // Parameter buffers associated with the staged command buffers
std::vector<webgpu_param_bufs> staged_param_bufs; std::vector<webgpu_param_bufs> staged_param_bufs;
std::vector<wgpu::FutureWaitInfo> callback_futures;
}; };
typedef std::shared_ptr<webgpu_context_struct> webgpu_context; typedef std::shared_ptr<webgpu_context_struct> webgpu_context;
@@ -221,25 +221,39 @@ static void ggml_webgpu_create_buffer(wgpu::Device & device,
/** WebGPU Actions */ /** WebGPU Actions */
// Wait for the queue to finish processing all submitted work
static void ggml_backend_webgpu_wait_on_submission(webgpu_context & ctx) { static void ggml_backend_webgpu_wait_on_submission(webgpu_context & ctx) {
// Wait for the queue to finish processing all commands std::lock_guard<std::recursive_mutex> lock(ctx->mutex);
ctx->instance.WaitAny(ctx->queue.OnSubmittedWorkDone( if (ctx->callback_futures.empty()) {
wgpu::CallbackMode::AllowSpontaneous, // no existing callbacks, wait on queue submission
[](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) { ctx->instance.WaitAny(ctx->queue.OnSubmittedWorkDone(
if (status != wgpu::QueueWorkDoneStatus::Success) { wgpu::CallbackMode::AllowSpontaneous,
GGML_LOG_ERROR("ggml_webgpu: Failed to wait on queue: %s\n", message.data); [](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) {
} if (status != wgpu::QueueWorkDoneStatus::Success) {
}), GGML_LOG_ERROR("ggml_webgpu: Failed to submit commands: %s\n", message.data);
UINT64_MAX); }
}),
UINT64_MAX);
} else {
// existing callbacks, wait on them
ctx->instance.WaitAny(ctx->callback_futures.size(), ctx->callback_futures.data(), UINT64_MAX);
ctx->callback_futures.clear();
}
} }
static void ggml_backend_webgpu_submit_queue(webgpu_context & ctx) { static void ggml_backend_webgpu_submit_queue(webgpu_context & ctx) {
std::lock_guard<std::recursive_mutex> lock(ctx->mutex); std::lock_guard<std::recursive_mutex> lock(ctx->mutex);
WEBGPU_LOG_DEBUG("ggml_backend_webgpu_submit_queue()");
if (ctx->staged_command_bufs.empty()) {
// Nothing to submit
return;
}
ctx->queue.Submit(ctx->staged_command_bufs.size(), ctx->staged_command_bufs.data()); ctx->queue.Submit(ctx->staged_command_bufs.size(), ctx->staged_command_bufs.data());
ctx->staged_command_bufs.clear(); ctx->staged_command_bufs.clear();
std::vector<webgpu_param_bufs> staged_param_bufs = std::move(ctx->staged_param_bufs); std::vector<webgpu_param_bufs> staged_param_bufs = std::move(ctx->staged_param_bufs);
// Free the staged parameter buffers once the submission completes // Free the staged parameter buffers once the submission completes
ctx->queue.OnSubmittedWorkDone( wgpu::Future f = ctx->queue.OnSubmittedWorkDone(
wgpu::CallbackMode::AllowSpontaneous, wgpu::CallbackMode::AllowSpontaneous,
[ctx, staged_param_bufs](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) { [ctx, staged_param_bufs](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) {
if (status != wgpu::QueueWorkDoneStatus::Success) { if (status != wgpu::QueueWorkDoneStatus::Success) {
@@ -248,6 +262,7 @@ static void ggml_backend_webgpu_submit_queue(webgpu_context & ctx) {
// Free the staged parameter buffers // Free the staged parameter buffers
ctx->param_buf_pool.free_bufs(staged_param_bufs); ctx->param_buf_pool.free_bufs(staged_param_bufs);
}); });
ctx->callback_futures.push_back({ f });
} }
static void ggml_backend_webgpu_map_buffer(webgpu_context & ctx, static void ggml_backend_webgpu_map_buffer(webgpu_context & ctx,
@@ -273,7 +288,7 @@ static void ggml_backend_webgpu_build_and_enqueue(webgpu_context &
std::vector<uint32_t> params, std::vector<uint32_t> params,
std::vector<wgpu::BindGroupEntry> bind_group_entries, std::vector<wgpu::BindGroupEntry> bind_group_entries,
uint32_t wg_x, uint32_t wg_x,
bool submit_imm = false) { bool submit_and_wait = false) {
webgpu_param_bufs params_bufs = ctx->param_buf_pool.alloc_bufs(); webgpu_param_bufs params_bufs = ctx->param_buf_pool.alloc_bufs();
ggml_backend_webgpu_map_buffer(ctx, params_bufs.host_buf, wgpu::MapMode::Write, 0, params_bufs.host_buf.GetSize()); ggml_backend_webgpu_map_buffer(ctx, params_bufs.host_buf, wgpu::MapMode::Write, 0, params_bufs.host_buf.GetSize());
@@ -304,17 +319,18 @@ static void ggml_backend_webgpu_build_and_enqueue(webgpu_context &
pass.DispatchWorkgroups(wg_x, 1, 1); pass.DispatchWorkgroups(wg_x, 1, 1);
pass.End(); pass.End();
wgpu::CommandBuffer commands = encoder.Finish(); wgpu::CommandBuffer commands = encoder.Finish();
if (submit_imm) { if (submit_and_wait) {
// Submit immediately // Submit and wait immediately
ctx->queue.Submit(1, &commands); ctx->queue.Submit(1, &commands);
ctx->queue.OnSubmittedWorkDone(wgpu::CallbackMode::AllowSpontaneous, ctx->instance.WaitAny(ctx->queue.OnSubmittedWorkDone(
[ctx, params_bufs](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) { wgpu::CallbackMode::AllowSpontaneous,
if (status != wgpu::QueueWorkDoneStatus::Success) { [ctx, params_bufs](wgpu::QueueWorkDoneStatus status, wgpu::StringView message) {
GGML_LOG_ERROR("ggml_webgpu: Failed to submit commands: %s\n", if (status != wgpu::QueueWorkDoneStatus::Success) {
message.data); GGML_LOG_ERROR("ggml_webgpu: Failed to submit commands: %s\n", message.data);
} }
ctx->param_buf_pool.free_bufs({ params_bufs }); ctx->param_buf_pool.free_bufs({ params_bufs });
}); }),
UINT64_MAX);
} else { } else {
// Lock the context mutex when pushing to the staging vectors. // Lock the context mutex when pushing to the staging vectors.
std::lock_guard<std::recursive_mutex> lock(ctx->mutex); std::lock_guard<std::recursive_mutex> lock(ctx->mutex);
@@ -579,6 +595,9 @@ static void ggml_backend_webgpu_buffer_set_tensor(ggml_backend_buffer_t buffer,
// memset the remaining bytes // memset the remaining bytes
ggml_backend_webgpu_buffer_memset( ggml_backend_webgpu_buffer_memset(
webgpu_ctx, buf_ctx->buffer, val32, total_offset + (size - remaining_size), remaining_size); webgpu_ctx, buf_ctx->buffer, val32, total_offset + (size - remaining_size), remaining_size);
} else {
// wait for WriteBuffer to complete
ggml_backend_webgpu_wait_on_submission(webgpu_ctx);
} }
} }
@@ -602,7 +621,7 @@ static void ggml_backend_webgpu_buffer_get_tensor(ggml_backend_buffer_t buffer,
final_size = size + (4 - (size % 4)); final_size = size + (4 - (size % 4));
} }
std::lock_guard<std::mutex> lock(webgpu_ctx->get_tensor_mutex); std::lock_guard<std::recursive_mutex> lock(webgpu_ctx->mutex);
if (webgpu_ctx->get_tensor_staging_buf == nullptr || webgpu_ctx->get_tensor_staging_buf.GetSize() < final_size) { if (webgpu_ctx->get_tensor_staging_buf == nullptr || webgpu_ctx->get_tensor_staging_buf.GetSize() < final_size) {
// Create a new staging buffer if it doesn't exist or is too small // Create a new staging buffer if it doesn't exist or is too small
@@ -768,10 +787,11 @@ static ggml_backend_t ggml_backend_webgpu_device_init(ggml_backend_dev_t dev, co
webgpu_context webgpu_ctx = dev_ctx->webgpu_ctx; webgpu_context webgpu_ctx = dev_ctx->webgpu_ctx;
// Multiple threads may try to initialize the device // Multiple threads may try to initialize the device
std::lock_guard<std::mutex> lock(webgpu_ctx->init_mutex); std::lock_guard<std::recursive_mutex> lock(webgpu_ctx->mutex);
if (!webgpu_ctx->device_init) { if (!webgpu_ctx->device_init) {
// Initialize device // Initialize device
std::vector<wgpu::FeatureName> required_features = { wgpu::FeatureName::ShaderF16, wgpu::FeatureName::ImplicitDeviceSynchronization }; std::vector<wgpu::FeatureName> required_features = { wgpu::FeatureName::ShaderF16,
wgpu::FeatureName::ImplicitDeviceSynchronization };
wgpu::DeviceDescriptor dev_desc; wgpu::DeviceDescriptor dev_desc;
dev_desc.requiredLimits = &webgpu_ctx->limits; dev_desc.requiredLimits = &webgpu_ctx->limits;
dev_desc.requiredFeatures = required_features.data(); dev_desc.requiredFeatures = required_features.data();