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authorGian Marco Iodice <gianmarco.iodice@arm.com>2018-10-18 10:21:02 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:55:45 +0000
commit4b90865ab985d571f70c60583cdfb8c7a65f1670 (patch)
treef116a4ffef5f5e823689dd00c1e5c9d987f3d295 /src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
parentc55beee7ef70fa08a5d217619083b288a74fcb27 (diff)
downloadComputeLibrary-4b90865ab985d571f70c60583cdfb8c7a65f1670.tar.gz
COMPMID-1413 - Improve the performance of GEMMLowp with 8 bit dot product on OpenCL
COMPMID-1424 - Add dot product support for CLDepthwise QASYMM8 3x3 NHWC non-unit stride With this patch we are able to improve the performance of MobileNet v1-qasymm8 by 37 % Tried to use the dot product instruction in CLDepthwise QASYMM8 3x3 NHWC non-unit stride but I have not seen any benefit (maybe because we have few arithemtic operation and we do not have more load instructions). However Depthwise convolution has been improved by 30% Change-Id: Id768a99c2e53a04276707e427af5d0ec93419ada Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/155082 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'src/runtime/NEON/functions/NEFullyConnectedLayer.cpp')
-rw-r--r--src/runtime/NEON/functions/NEFullyConnectedLayer.cpp3
1 files changed, 2 insertions, 1 deletions
diff --git a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
index 60f6294394..45e21b53d1 100644
--- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
+++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
@@ -50,6 +50,7 @@ Status validate_mm(const ITensorInfo &input, const ITensorInfo &weights, const I
// Validate gemmlowp function
ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpMatrixMultiplyCore::validate(&input.clone()->set_quantization_info(input_quantization_info),
&weights.clone()->set_quantization_info(weights_quantization_info),
+ nullptr,
&output));
}
else
@@ -93,7 +94,7 @@ void NEFullyConnectedLayer::configure_mm(const ITensor *input, const ITensor *we
weights->info()->set_quantization_info(QuantizationInfo(weights_quantization_info.scale, -weights_quantization_info.offset));
// Configure gemmlowp function
- _mm_gemmlowp.configure(input, weights, output);
+ _mm_gemmlowp.configure(input, weights, nullptr, output);
// Revert back QuantizatioInfo as input and weights could be used in other fully connected layers
input->info()->set_quantization_info(input_quantization_info);