blob: e5fbda7f94984ce178da55ff8220f449f8f3685a [file] [log] [blame]
/*
* Copyright 2022 Google LLC
*
* Use of this source code is governed by a BSD-style license that can be
* found in the LICENSE file.
*/
#include "tests/Test.h"
#include "include/gpu/graphite/Context.h"
#include "include/gpu/graphite/Recorder.h"
#include "include/gpu/graphite/Recording.h"
#include "src/gpu/graphite/Buffer.h"
#include "src/gpu/graphite/ComputePassTask.h"
#include "src/gpu/graphite/ComputePipelineDesc.h"
#include "src/gpu/graphite/ComputeTypes.h"
#include "src/gpu/graphite/RecorderPriv.h"
#include "src/gpu/graphite/ResourceProvider.h"
#include "src/gpu/graphite/SynchronizeToCpuTask.h"
using namespace skgpu::graphite;
DEF_GRAPHITE_TEST_FOR_RENDERING_CONTEXTS(ComputeTaskTest, reporter, context) {
constexpr uint32_t kProblemSize = 512;
constexpr float kFactor = 4.f;
std::unique_ptr<Recorder> recorder = context->makeRecorder();
// Construct a kernel that multiplies a large array of floats by a supplied factor.
ComputePipelineDesc pipelineDesc;
pipelineDesc.setProgram(
"layout(set=0, binding=0) readonly buffer inputBlock"
"{"
" float in_factor;"
" float in_data[];"
"};"
"layout(set=0, binding=1) buffer outputBlock"
"{"
" float out_data[];"
"};"
"void main() {"
" out_data[sk_GlobalInvocationID.x] = in_data[sk_GlobalInvocationID.x] * in_factor;"
"}",
"TestArrayMultiply");
ResourceProvider* provider = recorder->priv().resourceProvider();
sk_sp<Buffer> inputBuffer = provider->findOrCreateBuffer(
sizeof(float) * (kProblemSize + 1), BufferType::kStorage, PrioritizeGpuReads::kNo);
sk_sp<Buffer> outputBuffer = provider->findOrCreateBuffer(
sizeof(float) * kProblemSize, BufferType::kStorage, PrioritizeGpuReads::kNo);
std::vector<ResourceBinding> bindings;
bindings.push_back({/*index=*/0, {inputBuffer.get(), /*offset=*/0}});
bindings.push_back({/*index=*/1, {outputBuffer.get(), /*offset=*/0}});
// Initialize "in_data" to contain an ascending sequence of integers.
// Initialize "out_data" to "-1"s.
{
float* inData = static_cast<float*>(inputBuffer->map());
float* outData = static_cast<float*>(outputBuffer->map());
SkASSERT(inputBuffer->isMapped() && inData != nullptr);
SkASSERT(outputBuffer->isMapped() && outData != nullptr);
inData[0] = kFactor; // "in_factor"
for (unsigned int i = 0; i < kProblemSize; ++i) {
inData[i + 1] = i + 1;
outData[i] = -1;
}
inputBuffer->unmap();
outputBuffer->unmap();
}
ComputePassDesc desc;
desc.fLocalDispatchSize = WorkgroupSize(kProblemSize, 1, 1);
// Record the compute pass task.
recorder->priv().add(ComputePassTask::Make(std::move(bindings), pipelineDesc, desc));
// Ensure the output buffer is synchronized to the CPU once the GPU submission has finished.
recorder->priv().add(SynchronizeToCpuTask::Make(outputBuffer));
// Submit the work and wait for it to complete.
std::unique_ptr<Recording> recording = recorder->snap();
if (!recording) {
ERRORF(reporter, "Failed to make recording");
return;
}
InsertRecordingInfo insertInfo;
insertInfo.fRecording = recording.get();
context->insertRecording(insertInfo);
context->submit(SyncToCpu::kYes);
// Verify the contents of the output buffer.
{
float* inData = static_cast<float*>(inputBuffer->map());
float* outData = static_cast<float*>(outputBuffer->map());
SkASSERT(inputBuffer->isMapped() && inData != nullptr);
SkASSERT(outputBuffer->isMapped() && outData != nullptr);
for (unsigned int i = 0; i < kProblemSize; ++i) {
const float expected = inData[i + 1] * kFactor;
const float found = outData[i];
REPORTER_ASSERT(
reporter, expected == found, "expected '%f', found '%f'", expected, found);
}
inputBuffer->unmap();
outputBuffer->unmap();
}
}