COMPMID-734: CLTuner rework
Change-Id: I8f20d6ea8a09869d71003e7b08e0d33775282f6c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/125802
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/runtime/CL/CLScheduler.cpp b/src/runtime/CL/CLScheduler.cpp
index 65292fe..2a5d836 100644
--- a/src/runtime/CL/CLScheduler.cpp
+++ b/src/runtime/CL/CLScheduler.cpp
@@ -52,7 +52,7 @@
if(_cl_tuner != nullptr)
{
// Tune the OpenCL kernel
- _cl_tuner->tune_kernel(kernel);
+ _cl_tuner->tune_kernel_dynamic(kernel);
}
// Run kernel
diff --git a/src/runtime/CL/CLTuner.cpp b/src/runtime/CL/CLTuner.cpp
index df8e255..17a62ab 100644
--- a/src/runtime/CL/CLTuner.cpp
+++ b/src/runtime/CL/CLTuner.cpp
@@ -113,7 +113,12 @@
return _tune_new_kernels;
}
-void CLTuner::tune_kernel(ICLKernel &kernel)
+void CLTuner::tune_kernel_static(ICLKernel &kernel)
+{
+ ARM_COMPUTE_UNUSED(kernel);
+}
+
+void CLTuner::tune_kernel_dynamic(ICLKernel &kernel)
{
// Get the configuration ID from the kernel
const std::string &config_id = kernel.config_id();
diff --git a/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp b/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp
index d6a335c..c48865a 100644
--- a/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -52,6 +52,9 @@
zero_value = PixelValue(static_cast<uint8_t>(input->info()->quantization_info().offset));
}
_input_border_handler.configure(input, _direct_conv_kernel.border_size(), BorderMode::CONSTANT, zero_value);
+
+ // Tune kernels
+ CLScheduler::get().tune_kernel_static(_direct_conv_kernel);
}
Status CLDirectConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info)
diff --git a/src/runtime/CL/tuners/BifrostTuner.cpp b/src/runtime/CL/tuners/BifrostTuner.cpp
new file mode 100644
index 0000000..c0ebd24
--- /dev/null
+++ b/src/runtime/CL/tuners/BifrostTuner.cpp
@@ -0,0 +1,143 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/runtime/CL/tuners/BifrostTuner.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernels.h"
+#include "arm_compute/core/utils/misc/Cast.h"
+
+namespace arm_compute
+{
+namespace tuners
+{
+namespace
+{
+/** Tunes a @ref CLDirectConvolutionLayerKernel for a bifrost target
+ *
+ * @param[in] k Kernels to tune
+ */
+void tune_direct_convolution_kernel(CLDirectConvolutionLayerKernel &k)
+{
+ cl::NDRange lws_hint = k.lws_hint();
+
+ const GPUTarget gpu_target = k.get_target();
+ const DataType dt = k._input->info()->data_type();
+ const TensorShape weights_shape = k._weights->info()->tensor_shape();
+ const TensorShape inputs_shape = k._input->info()->tensor_shape();
+ const size_t kernel_size = weights_shape.x();
+ const unsigned int stride_x = k._conv_stride_x;
+ const unsigned int stride_y = k._conv_stride_y;
+
+ if(gpu_target_is_in(gpu_target, GPUTarget::G71, GPUTarget::G72) && (kernel_size <= 5) && (stride_x == 1) && (stride_y == 1) && (dt == DataType::F32))
+ {
+ // Through extensive experimentation with over 30 representative tensor
+ // shapes, we found a small number of local work size configurations
+ // that result in nearly optimal execution times. Selecting the right
+ // lws for a given shape, however, required a complex decision tree,
+ // until we constructed a simple feature as described below.
+ //
+ // We started from the number of multiply-accumulate operations for a
+ // convolution layer, which is equal to the product of the input
+ // dimensions 0..2 and the weights dimensions 0..2. Unfortunately,
+ // this resulted in ties between distinct shapes that required distinct
+ // lws configurations. Replacing the width of the input with the kernel
+ // size, however, resulted in nearly optimal predictions. We use underscores
+ // in variable names to indicate when they are intentionally misleading.
+ const size_t product_of_weights_dimensions = weights_shape[0] * weights_shape[1] * weights_shape[2];
+ const size_t product_of_input_dimensions_ = inputs_shape[0] * inputs_shape[1] * inputs_shape[2];
+ const float mega_ops_ = 1e-6 * product_of_weights_dimensions * product_of_input_dimensions_;
+
+ switch(kernel_size)
+ {
+ case 1:
+ {
+ if(mega_ops_ < 1.f)
+ {
+ lws_hint = cl::NDRange(1, 1, 8);
+ }
+ else if(mega_ops_ < 7.f)
+ {
+ lws_hint = cl::NDRange(1, 1, 4);
+ }
+ else
+ {
+ lws_hint = cl::NDRange(1, 1, 2);
+ }
+ break;
+ }
+ case 3:
+ {
+ if(mega_ops_ < 1.f)
+ {
+ lws_hint = cl::NDRange(1, 1, 8);
+ }
+ else if(mega_ops_ < 13.f)
+ {
+ lws_hint = cl::NDRange(2, 1, 4);
+ }
+ else if(mega_ops_ < 50.f)
+ {
+ lws_hint = cl::NDRange(3, 1, 4);
+ }
+ else
+ {
+ lws_hint = cl::NDRange(2, 1, 6);
+ }
+ break;
+ }
+ case 5:
+ {
+ if(mega_ops_ < 2.f || mega_ops_ > 80.f)
+ {
+ lws_hint = cl::NDRange(2, 1, 4);
+ }
+ else
+ {
+ lws_hint = cl::NDRange(2, 1, 8);
+ }
+ break;
+ }
+ default:
+ break;
+ }
+ k.set_lws_hint(lws_hint);
+ }
+}
+} // namespace
+
+void BifrostTuner::tune_kernel_static(ICLKernel &kernel)
+{
+ // Continue on tuning if dynamic tuning
+ if(dynamic_cast<CLDirectConvolutionLayerKernel *>(&kernel) != nullptr)
+ {
+ tune_direct_convolution_kernel(*utils::cast::polymorphic_downcast<CLDirectConvolutionLayerKernel *>(&kernel));
+ }
+}
+
+void BifrostTuner::tune_kernel_dynamic(ICLKernel &kernel)
+{
+ ARM_COMPUTE_UNUSED(kernel);
+}
+} // namespace tuners
+} // namespace arm_compute
\ No newline at end of file