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This patch introduces several performance optimizations regarding the Bilinear Scale operator with REPLICATE Border mode. Changes apply only to NHWC.
This patch
- Reduces the memory footprint by disabling precomputation of indices and weights when they're not used
- Rewrites the kernels for QASYMM8/QASYMM8_SIGNED/U8(Uint8)
- Adds S8(Int8) Bilinear Scale for Border mode REPLICATE
- Removes Bilinear Scale SVE kernels for Quantized and Integer types and adjust the heuristics to choose the Neon™ implementation
- Adds new test cases where the input and output of the Bilinear Scale operator have different quantization scale and offset
Resolves: COMPMID-5453, COMPMID-5454
Change-Id: I3d251e76e0c6978fd5a0a1795ec62ab536bec93c
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8250
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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* Also fix a bug in mul_U8_U8_U8.
Resolves: COMPMID-5460
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: Ie1edafeae7aaad91164caeeb04661a8974a7fc1b
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8244
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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The M0 and N0 were incorrectly set for the case of broadcasting when the
elementwise component is non-root.
This is because we previously always use rhs tensor to derive the load
M0, N0. But for non-root components, the addend/divisor tensor can be
in the lhs or rhs. Thus this would fail in case the addend/divisor is in
the lhs.
- Also fixes broken Dynamic Fusion test
Resolves COMPMID-5482
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: I37f27ffa392781387db15739b1666f1dad28c554
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/445890
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Mohammed Suhail Munshi <mohammedsuhail.munshi@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8111
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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OpenCL implementation uses built in erf.
NEON implementation requires new vectorized erf.
Uses the following approximation:
erf(x) = 1 - 1 / (1 + a1x + a2x^2 + a3x^3 + a4x^4)^4
a1 = 0.278393, a2 = 0.230389, a3 = 0.000972, a4 = 0.078108
From https://en.wikipedia.org/wiki/Error_function#Numerical_approximations
Signed-off-by: Murray Kornelsen <murray.kornelsen@mail.mcgill.ca>
Change-Id: I2d3964b2c26a4334166b17135f9104bc6324fad2
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7921
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Pablo Marquez Tello <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Implements LayerNorm for qasymm8 tensors.
Uses uint8x16 loads and stores.
Summation is performed in integer arithmetic (vpaddl)
Normalization is performed in float32 before requantizing back to int8.
Signed-off-by: Murray Kornelsen <murray.kornelsen@mail.mcgill.ca>
Change-Id: I2407c8b34717fb47adab98791bd76fb8a3c62f4a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7922
Comments-Addressed: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Resolves: COMPMID-5531
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: Id1a5f909d64e897cdef2e920240ac5ae244166b4
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8242
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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input tensors
- Add a test for CPU to batched matrix multiplication with variable input tensors
- Disable assembly kernel when using _reshape_b_only_on_first_run flag
Resolves COMPMID-5501
Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com>
Change-Id: If96b182584617806a9dfe597dbfaf05241b123c2
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8234
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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The heuristic has been tweaked to call direct convolution when we think
it can be faster than gemm-based convolution. The main change is
affecting the selection of the convolution method on the first layer.
In general, the question we should ask for the first convolution layer of
a model is: when the execution time of im2col + gemm < direct?. Since
im2col does not depend on the OFM, it means that when OFM is big enough,
the contribution of im2col is small and the GEMM approach is preferable.
From internal experiments, the OFM threshold is 64.
Resolves COMPMID-5504, COMPMID-5504, COMPMID-5477
Change-Id: If1bd1fa93c185ffa874388e29866244e62ca3494
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8231
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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This patch removes index and weight pre-computations where it's not used and reduces some calculations inside the inner-most loop of Scale.
Resolves: COMPMID-5452
Change-Id: Ie149b1b76a90a8cb659ada0f97aef78caf69932f
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8220
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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Resolves COMPMID-5498
Change-Id: I474f3f963257014255d082aab0ccbe3efe5aa067
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8222
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Ramy Elgammal <ramy.elgammal@arm.com>
Reviewed-by: Ramy Elgammal <ramy.elgammal@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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- That would force CpuConv2d::get_convolution_method()
choose GEMM_CONV2D or GEMM methods instead.
Resolves: COMPMID-5531
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I4dec8772e8c150da003d9a89c1d036057c4d28b0
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8233
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
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The optimization concerns the case where the depth multiplier is > 1.
The depth multiplier for loop has been removed from the OpenCL kernel
and the GWS has been mapped to the output shape. In this way, we can
still perform a tile with N0 columns and improve the performance of
depthwise conv over 80% when depth multiplier is > 1.
Resolves COMPMID-5568
Change-Id: I604e287d4eeb31c54b9cc6c3072a698cd0e3e136
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8184
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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input tensors
Resolves : [COMPMID-5502]
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: Ida001dc597973f9180468737a3e32e5022e6baee
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/450342
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Mohammed Suhail Munshi <mohammedsuhail.munshi@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8224
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Ran into issues with f16 meanstddevnorm. Essentially, with large enough tensors and/or large values in tensors, output becomes all 0.
This is due to the variance computation. In f16, it reaches infinity quite easily, then the division results in 0.
This change modifies the OpenCL and NEON implementations to compute the sum of squares and the variance using f32, while other operations remain f16.
Update: Found that the square operation also benefits from f32, rather than squaring in f16 and accumulating f32.
Signed-off-by: Murray Kornelsen <murray.kornelsen@mail.mcgill.ca>
Change-Id: Ide00afd84ec6d26fec4d53b073e295814f08ba46
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7959
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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From an internal performance evaluation, it seems that Winograd-based
Conv2D offers better performance than alternative methods such as direct
convolution and gemm-based conv already from IFM=8. Before the condition
was for IFM>=16
Resolves COMPMID-5532
Change-Id: I9ff04835d6fd07f5f0abeec9645c9d9cc913b6b7
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8147
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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* Resolves COMPMID-5211
Change-Id: I7cc72662bb1cf52bf112685639d3dbba33d1333f
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7993
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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repeatedly when mapping multiple children of the same parent.
Signed-off-by: Murray Kornelsen <murray.kornelsen@mail.mcgill.ca>
Change-Id: I7ff554915a37320dfd94f15a6fb01a72a235cf39
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7920
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Previously, the add_as_1d_array kernels were used on tensors with
non-matching strides which caused the wrong elements to be added. The
fix is to check that the strides are equal when selecting the addition
kernel.
Change-Id: I914ca2b95e5b8ed1875ec5ebe129bdfe2845496b
Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8120
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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* Resolves MLCE-799
Change-Id: I3d5b2afbf65d159aa5e645743c1e139110dfc20e
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8093
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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* Resolves MLCE-903
Change-Id: I39fb3b4b395a37c0f32481830f94d85ec15e205f
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8124
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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Removes FP Bilinear SVE kernels and uses Neon™ kernels instead
Resolves: COMPMID-5449
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Change-Id: I8e01de44bd884cb6578ca0b9358509b69bc31ca2
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8100
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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- Reverting commit e54d8c07e75d70baeb80fecbb43088027ea45658
because it has caused unexpected regressions.
Resolves: COMPMID-5504
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I2a0bcc6a311009a81f20a146079758ad138fff5b
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8092
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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* Move LUT implementation to a seperate file. It will be used
for both QASYMM8 and QASYMM8_SIGNED.
* Fix wrong constant value related to QASYMM8_SIGNED leaky ReLU
in 32-bit build.
Resolves: COMPMID-5464
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I2b24d52409a38f1b66fd532f431eff8a9e4547b6
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8066
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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- Call gemm-based convolution when the kernel is large and the stride is
unit
Resolves: COMPMID-5504
Change-Id: I8dd83bd012000ed76824b96a8e37c98c861c59e4
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8081
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Adnan AlSinan <adnan.alsinan@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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Partially Resolves: COMPMID-5346
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I26212bfb46cd451ef01956ade0a306bbdbf5940e
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8069
Reviewed-by: Adnan AlSinan <adnan.alsinan@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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Partially Resolves: COMPMID-5346
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: Ida1ad7ff19837203b3366466ba8018386cd6b18f
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8065
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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- Affect CL backend.
- For FP32 datatype, affect different platforms.
Resolves COMPMID-5479
Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com>
Change-Id: I705d718bc9b7def218034958f7ef86f2c2abe06d
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8064
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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The unsafe FP optimizations flag causes accuracy issues when certain conditions are met regarding the hardware type, data type and the activation function.
Resolves: COMPMID-5375
Change-Id: I1b0b06549b8c108617962d006a20dd263d5e3c21
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8061
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Partially Resolves: COMPMID-5346
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I41755295450b6ee698d8998d8a6d6bf9d4e4e7a9
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/443006
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Sicong Li <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8052
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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The issue is caused by GPUTarget not being set explicitly
for the Depthwise convolution kernel, but it's being used
in its build configuration. This causes the default value
to be used and enables some unsafe FP optimizations.
Resolves: COMPMID-5490
Change-Id: I5300a1168962cacb62cf49db795f052cf6740c7e
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8059
Reviewed-by: SiCong Li <sicong.li@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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* For 3x3 kernel, only choose the implementation with larger tile
size if the input tensor is larger than the tile.
Resolves: COMPMID-5467
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I2cf95ddb25f477cb05da3b3501e0afe9548fc33a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8022
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Resolves: COMPMID-5345
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I2fe4cb16bddf0f6a25906ab471e0a684d9ddf0ec
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8050
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
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Partially Resolves: COMPMID-5346
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I1740d3244d7fcaf58613bbb508db7b46ba13f19e
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8045
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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Resolves COMPMID-5420
Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com>
Change-Id: I24dca916f49f82e7e5ec809500ae5fe32c8adc97
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8020
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Minor tweaks and test for running fixed format kernels with BF16
operations when specified by the user.
Change-Id: Ic8167f67b86b1298da65e46cfebed9f3b86940e4
Signed-off-by: Milos Puzovic <milos.puzovic@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8000
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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- Allow fusing arbitrary number of existing elementwise operators
- Fix issues with 3D and 4D tensors in Elementwise Addition and Floor components
- Collapse the 3D/4D window in the same way as that used by Conv2d,
i.e. collapse dim 1 and dim 2 together
- Fix Floor component issues when used after other components
- Add Dynamic Fusion Tests (Floor + Div, Conv2d + Add + Div)
- Add Addition ElementWise Broadcasting Test
Resolves: [COMPMID-5356]
Change-Id: I58b93a90175bb0440d43531d18cac94b5f5c2689
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/433956
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7957
Reviewed-by: SiCong Li <sicong.li@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Implements required plumbing in order to be able to ask and execute
fixed format kernels from NEFullyConnected, NEGEMM and NEGEMMConv2d.
These APIs are used to accelerate oneDNN primitives (inner product, matrix
multiplication and indirect GEMM respectively) and without changes it
would not be possible to call fixed format kernels from those oneDNN
primitives.
Change-Id: I27534f0491ce28d0ccb98c19f318bd33dcdf2ff5
Signed-off-by: Milos Puzovic <milos.puzovic@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7999
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Resolves COMPMID-5405
Change-Id: I995b5e79bef13529097ed17f7854763a4cf89272
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7986
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Resolves: COMPMID-5108
Change-Id: I544f8160fbe5b4ffbef348d1fbd3dd626a6e1bdb
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8002
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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If number of work items is greater than number of available threads then
OpenMP scheduler will only execute as many work items as there are
threads. This fix makes sure that we iterate through all work items and
execute all of them.
Change-Id: I3ad4b732c01fadc70dacaf09af3007d2b31086c7
Signed-off-by: Milos Puzovic <milos.puzovic@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8001
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
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Resolves: COMPMID-5402
Change-Id: Ic4abda36c475c3a7d86fb469d7ed1b23a62ea182
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7991
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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* Fixed an error caused by a newline missing in line 187
* Added section about building natively on Windows on ARM
* Resolves MLCE-739
Change-Id: I2f452d77247b2a264e7f122d97cbb8f288716971
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7992
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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- related to 91780021e2 Fix for inclusion of "arm_gemm"
- arm_compute::WeightFormat was passed to a function
expecting arm_gemm::WeightFormat
Resolves: COMPMID-5415
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: Ib53fad2eab0148f466a5e2f11b931754569da3d6
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7989
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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* Resolves COMPMID-5422
Change-Id: Ib59d85aead3f8f9559392957fbc42a4ddbb27b07
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/440126
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7987
Benchmark: Arm Jenkins <bsgcomp@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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- Added arm_compute::WeightFormat and converted to/from arm_gemm::WeightFormat
when needed through two map function.
- Moved to_string(WeightFormat) to TypePrinter.h
Resolves: COMPMID-5415
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I65f7942100bcd4dbf2c5cf6c07f26c8e1e3bf86e
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/438511
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-by: Sicong Li <sicong.li@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7985
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Since Android™ 13, the underlying NDK has deprecated system assembler
and favors integrated assembler instead
Please also see https://github.com/android/ndk/wiki/Changelog-r23
Resolves COMPMID-5410
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: Ib9fa8a22f6cdb5cb4f0095e15bf332484f709630
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7956
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-by: Ramy Elgammal <ramy.elgammal@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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* scons arch=armv8.6-a translates to -march=armv8.6-a
* scons arch=armv8.6-a-sve translates to -march=armv8.6-a+sve
* scons arch=armv8.6-a-sve2 translates to -march=armv8.6-a+sve2
* Resolves COMPMID-5408
Change-Id: I0901e1de864d00109759509af7cc2b5c9ae1cd75
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7943
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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* Resolves MLCE-888
Change-Id: I90291cb5f6eddbb889e86dd3295ff8b05b1e1311
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7953
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
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This patch introduces a GEMMLowp routine that is optimized for Arm(R) Mali(TM)-G715 and Arm(R) Mali(TM)-G615
Resolves: COMPMID-5398
Signed-off-by: Freddie Liardet <frederick.liardet@arm.com>
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Change-Id: I8d06453645688f3658b6c7c06f1ebc25a2505661
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7932
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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Resolves COMPMID-5298
Change-Id: I4a7d788bc1f5f568bedcc22e7aca47ede6de71bf
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7891
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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