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- Only CLKernels have been updated
Change-Id: Ife55b847c2e39e712a186eb6ca452503d5b66937
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3001
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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Split out the parts of ToolchainSupport coming from <memory> and
the parts coming from <string> into their own new header files.
This accounts for 99% of uses of ToolchainSupport, which means that
expensive header files such as arm_neon.h don't need to be included
everywhere.
Knocks about 10% of compilation time off kernel files.
Signed-off-by: Matthew Bentham <matthew.bentham@arm.com>
Change-Id: I2ae718fe766b5ff28608812b0f686f30eeac1b21
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2852
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
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Change-Id: I8675b4b4face0be9416ae6c7a7023234d50fc0cb
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1524
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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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>
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Change-Id: Ib14ac821ee5d4aff80bd602cd3e76e7018abb5e6
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/150268
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
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This causes problems when ACL is used as a shared library on Android.
Fixes some problems related to creation / destruction order between the Graph's CL backend and core / runtime
Change-Id: I716d63fd42f4586df1ffbb6fa97e4db06d3a781b
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/143228
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
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This new optimization allows to achieve 36.3 % of MAC utilisation on Mate 9 @ 1GHz.
The performance have been reported here
https://confluence.arm.com/display/MLENG/GEMMLowp+performance%3A+ACL+18.02
Change-Id: I71b6a217068763dfdc11bbf3574ee0eb94f93679
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118531
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
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Change-Id: I4d2eb9872a3165fdcaa7784596e441cbe563dbc2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/112577
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Ioan-Cristian Szabo <ioan-cristian.szabo@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
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Change-Id: Id69df4ce98d1d89bdf9c9aa5c4d909659909b30f
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110456
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
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Change-Id: I70e04d3a175ba366432ada98e9ca893c9f81b260
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111094
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
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Reworked the interface of GemmLowp in order to make easy the integration
in Android NN
- Added support for different output stage
- Added validation for both matrix multiplication and output stage
- Added bounded relu support in the output stage
- Added in32_t bias support
- Added optimized path for vector by matrix case
This rework is required for:
- Convolution quantized
- Fully connected quantized
Change-Id: I512283d406099cf8c614dd89d0a97ed411143afc
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110625
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
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