718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
174 lines
3.3 KiB
Markdown
174 lines
3.3 KiB
Markdown
## supported platform
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* Y = known work
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* ? = shall work, not confirmed
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* / = not applied
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| |windows|linux|android|mac|ios|
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|---|---|---|---|---|---|
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|intel|Y|Y|?|?|/|
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|amd|Y|Y|/|?|/|
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|nvidia|Y|Y|?|/|/|
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|qcom|/|/|Y|/|/|
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|apple|/|/|/|?|Y|
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|arm|/|?|?|/|/|
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## enable vulkan compute support
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```
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$ sudo dnf install vulkan-devel
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$ cmake -DNCNN_VULKAN=ON ..
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```
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## enable vulkan compute inference
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```cpp
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ncnn::Net net;
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net.opt.use_vulkan_compute = 1;
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```
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## proper allocator usage
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```cpp
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ncnn::VkAllocator* blob_vkallocator = vkdev.acquire_blob_allocator();
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ncnn::VkAllocator* staging_vkallocator = vkdev.acquire_blob_allocator();
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net.opt.blob_vkallocator = blob_vkallocator;
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net.opt.workspace_vkallocator = blob_vkallocator;
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net.opt.staging_vkallocator = staging_vkallocator;
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// ....
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// after inference
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vkdev.reclaim_blob_allocator(blob_vkallocator);
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vkdev.reclaim_staging_allocator(staging_vkallocator);
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```
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## select gpu device
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```cpp
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// get gpu count
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int gpu_count = ncnn::get_gpu_count();
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// set specified vulkan device before loading param and model
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net.set_vulkan_device(0); // use device-0
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net.set_vulkan_device(1); // use device-1
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```
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## zero-copy on unified memory device
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```cpp
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ncnn::VkMat blob_gpu;
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ncnn::Mat mapped = blob_gpu.mapped();
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// use mapped.data directly
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```
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## hybrid cpu/gpu inference
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```cpp
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ncnn::Extractor ex_cpu = net.create_extractor();
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ncnn::Extractor ex_gpu = net.create_extractor();
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ex_cpu.set_vulkan_compute(false);
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ex_gpu.set_vulkan_compute(true);
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#pragma omp parallel sections
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{
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#pragma omp section
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{
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ex_cpu.input();
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ex_cpu.extract();
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}
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#pragma omp section
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{
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ex_gpu.input();
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ex_gpu.extract();
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}
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}
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```
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## zero-copy gpu inference chaining
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```cpp
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ncnn::Extractor ex1 = net1.create_extractor();
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ncnn::Extractor ex2 = net2.create_extractor();
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ncnn::VkCompute cmd(&vkdev);
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ncnn::VkMat conv1;
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ncnn::VkMat conv2;
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ncnn::VkMat conv3;
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ex1.input("conv1", conv1);
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ex1.extract("conv2", conv2, cmd);
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ex2.input("conv2", conv2);
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ex2.extract("conv3", conv3, cmd);
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cmd.submit();
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cmd.wait();
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```
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## batch inference
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```cpp
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int max_batch_size = vkdev->info.compute_queue_count;
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ncnn::Mat inputs[1000];
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ncnn::Mat outputs[1000];
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#pragma omp parallel for num_threads(max_batch_size)
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for (int i=0; i<1000; i++)
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{
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ncnn::Extractor ex = net1.create_extractor();
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ex.input("data", inputs[i]);
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ex.extract("prob", outputs[i]);
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}
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```
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## control storage and arithmetic precision
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disable all lower-precision optimizations, get full fp32 precision
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```cpp
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ncnn::Net net;
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net.opt.use_fp16_packed = false;
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net.opt.use_fp16_storage = false;
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net.opt.use_fp16_arithmetic = false;
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net.opt.use_int8_storage = false;
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net.opt.use_int8_arithmetic = false;
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```
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## debugging tips
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```cpp
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#define ENABLE_VALIDATION_LAYER 1 // modify to 1 in gpu.cpp
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```
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## add vulkan compute support to layer
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1. add vulkan shader in src/layer/shader/
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2. upload model weight data in Layer::upload_model()
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3. setup pipeline in Layer::create_pipeline()
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4. destroy pipeline in Layer::destroy_pipeline()
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5. record command in Layer::forward()
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## add optimized shader path
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1. add vulkan shader in src/layer/shader/ named XXX_abc.comp
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2. create pipeline with "XXX_abc"
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3. record command using XXX_abc pipeline
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## low-level op api
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1. create layer
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2. load param and load model
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3. upload model
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4. create pipeline
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5. new command
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6. record
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7. submit and wait
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