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2024-04-15Add s8f32 kernels and dynamic QuantizationInfoJonathan Deakin
- Add support for QASYMM_SIGNED*QASYMM8_SIGNED->F32 in CpuGemmLowpMatrixMultiplyCore - Add s8f32 kernel using existing s8->s32 kernels with a new DequantizeFloat OutputStage, the structure is similar to Requantize32 but the opposite way around. - Add SME s8f32 kernels with integrated support for DequantizeFloat. - Add scale to CpuGemmLowpOffsetContributionKernel. - Add virtual dequantize scale to gemm_common, only implemented for gemm_interleaved. - Update year to 2024 in generate_build_files. - Add dynamic flag to QuantizationInfo which signals to operators that it can change after configuration - Add support for dynamic quantization in NEGEMMLowpMatrixMultiplyCore - Add dynamic quantization fixture by extending GEMMLowpGenericMatrixMultiplyCoreValidationFixture - Add GEMMLowpDequantizedMatrixMultiplyValidationFixture - Store k (number of cols of A) rather than k_offset in the offset contribution kernels so that we can recompute it when the other offsets change relates to: ONCPUML-1444 MLINFSW-439 Co-authored-by: Milos Puzovic <Milos.Puzovic@arm.com> Co-authored-by: David Mansell <David.Mansell@arm.com> Change-Id: I58a3acf2c09289a303e52eea6b336a696a5bc8da Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11022 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>
2024-04-12Accumulation in Cpu Gemm kernels is not supported for quantized kernels in ↵Radu Salavat
aarch32. This patch guards the relevant tests. Partially Resolves: ONCPUML-1442 Signed-off-by: Radu Salavat <radu.salavat@arm.com> Change-Id: I8eed80db4b522185c3c50c13f0f701aa48961057 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11410 Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2024-04-11Add in place summation to CPU GEMM kernelsRadu Salavat
Instead of dispatching the sum postop for GEMM kernels to a separate kernel + add, that requires an extra destination sized allocation, plus 3 extra load/stores per element, just do it in the GEMM kernel. Resolves: ONCPUML-1442 Signed-off-by: Radu Salavat <radu.salavat@arm.com> Co-authored-by: Milos Puzovic <milos.puzovic@arm.com> Change-Id: I7a1f2da3300875fa1ac88b705a34390969518077 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11298 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>
2024-04-04Parallelise im2col along dimensions with higher number of iterationsMilos Puzovic
Signed-off-by: Milos Puzovic <milos.puzovic@arm.com> Change-Id: I362f3f4a42e218424fca917bed22003ec9d5609c Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11363 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
2024-03-21[ONCPUML-1451] Add matmul kernel to enable bf16 to bf16 operations via ↵Renato Arantes
PyTorch® autocast() function The full range of tests must be added with [MLINFSW-482] epic due to the lack of reordering kernels implemented in Acl. Co-Authored-By: David Mansell <David.Mansell@arm.com> Change-Id: I820d316295a1ec94fdc89c37e4144a268f914c36 Signed-off-by: Renato Arantes <renato.arantes@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11169 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>
2024-03-12Optimize CpuSoftmaxKernel for axis != 0 and neon kernelsOmar Al Khatib
Resolves: COMPMID-6501 Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Change-Id: I0abd3cbb5f861301f407c443988fb7efaa205b5d Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11056 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>
2024-03-11Prefer indirect Gemm vs. Direct convolution if supportedGunes Bayir
Indirect GEMM uses optimized assembly path while Direct Conv uses the fallback Acl kernel for convolution. In certain cases, where the input tensor is large and filter size is greater than 7 (e.g. 9x9 filters), heuristics fall back to Direct Conv algorithm where it could still prefer the assembly path if the data layout is NHWC. This is more important when SME2 kernels are present. Resolves: COMPMID-6900 Change-Id: Ia611c975eee0423615113fcaeaa8f9eef0421456 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11254 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Anitha Raj <Anitha.Raj@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2024-03-04Fix performance regression in fixed-format kernelsGunes Bayir
Fix the performance regression in CpuGemmConv2d caused by importing memory at every run for fixed-format kernels. This has been done by adding an bypass_import parameter to the aux. tensor handler class (CpuAuxTensorHandler) and using it in CpuGemmConv2d so that the memory import happens if and only when the associated tensor is used in the gemm pack. Also, improve the documentation of CpuAuxTensorHandler. Resolves: ARMCL-1126 Co-authored by: SiCong Li <sicong.li@arm.com> Change-Id: Idb26bdb2d19419074a6e7f2497a1741ae200603f Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11240 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2024-02-21Integrate new pretranspose_b_array with extra fused transpose of BGunes Bayir
This patch fuses the transposition taking place in Acl with the transformations done in arm_gemm (called pretranspose_b_array) if the underlying kernel and transform supports it. This should improve start-up time (as it's for constant Rhs matrices) and memory footprint. The transformations in arm_gemm are kernel specific. The Rhs matrix is transformed into certain layouts to improve the performance. Resolves: COMPMID-6595 Change-Id: Id2932dd966e59f903c279417bebcea83d9a42464 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11144 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2024-02-20Requantization cases for offset changes onlyMohammed Suhail Munshi
Resolves: [COMPMID-6681] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I325b9d478dd1d04a45533bb7708cf76e98ee0cee Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11058 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>
2024-02-12Fix parallel depthwise perf regression from 2db938cJonathan Deakin
Incorrect conditional meant that we were parallelizing over batches when we should have been parallelizing over rows. Relates to: ONCPUML-1443 COMPMID-6875 Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com> Change-Id: I61d43bb2a94e8a6887d4cc5d1ae2ebb03295dff7 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11120 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2024-02-07Parallelize CPU depthwise over batch if only 1 rowJonathan Deakin
This patch also fixes a bug where the split dimension was wrong in CpuDepthwiseConv2dAssemblyDispatch::run. It was set to DimY, which is cols, but it should have been DimZ. This was rarely an issue in practice because typically the number of cols are greater than the number of threads anyway. Relates to: ONCPUML-1443 Co-authored-by: Milos Puzovic <Milos.Puzovic@arm.com> Change-Id: Ifed2fce22ddeb7cd77e6a6ae1083694427f91e04 Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11083 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-12-12Winograd changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Changes in filelist.json: moved fp16 code from common to fp16 * Replaced the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC with ENABLE_FP16_KERNELS. * Resolves COMPMID-6755 Change-Id: I4da1c53d3f9e4734e5e67125265ab4e3fc0dcbe4 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10865 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-12-06Revert "thread_local _custom_scheduler"Pablo Marquez Tello
This reverts commit ded5b182675e3166e947a8eb637b5b1e925816ab. Resolves COMPMID-6735 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Change-Id: I9b69ca1ec80a671171d3f52081c4b8c61a676617 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10838 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: <felixjohnny.thomasmathibalan@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-12-05Optimize CpuSoftmaxKernel for axis=0Gunes Bayir
Implement a single kernel instead of having two consecutive ones. In the previous setup, one kernel was calculating the maximum value in the axis, and this maximum was being subtracted from each data while calculating the softmax, i.e. softmax(x_i) = exp(x_i - max) / sum_i( exp(x_i - max) ) This patch integrates these two stages into a single kernel for Neon™ for all data types. This will save some memory because we don't need to hold the max values in a separate auxiliary tensor. It also introduces some other optimizations that will ease memory pressure when the data type is float/half, by using the dst tensor as temporary storage for already exponentiated inputs. It removes the references to SVE and SVE2 implementations, and most of the associated files; but, it leaves the implementations as these may be used in the future. Resolves: COMPMID-6500 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: Icff9976d1214c4c6cbe15a62ca60b8a77d3784cc Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10688 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>
2023-11-24thread_local _custom_schedulerDavid Svantesson
Resolves ONCPUML-1331 This patch adds an option to make _custom_scheduler thread_local to support usage of multiple schedulers handled outside of ACL. It also adds num_threads() function to Scheduler which reverts to querying CPUInfo if no scheduler has been set. Change-Id: Iff706165d8d091895331a5bb3a76f6cabe048912 Signed-off-by: David Svantesson-Yeung <david.svantesson-yeung@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10748 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>
2023-11-15Fix various coverity issuesSiCong Li
Resolves COMPMID-6677 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: I99bf2385f6edc0836faacb31f5c66ed4fb051e40 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10729 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-11-10Fix CpuGemmConv2d int8 segfaultSiCong Li
Bypass importation of memory of the original weights into the reinterpreted_weights auxiliary tensor if other weight transformation path is selected (which would've freed the original weights and its tensor info) Resolves COMPMID-6635 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: Ib8a345c3ac542bc3745d6a67db822b55df37e827 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10698 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Anitha Raj <Anitha.Raj@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-11-08Optimize CpuGemmConv2d start-up timeSiCong Li
When weight has no holes, we can replace CpuWeightsReshapeKernel with: - Collapse by reinterpreting weight's 3 spatial dimensions - Perform CpuTranspose For more details see the documentation in src/cpu/operators/CpuGemmConv2d.cpp This is one optimization since the CpuTranspose is better performing than CpuWeightsReshapeKernel A second optimization is to fuse this transpose with other weight transformations (e.g. pretranspose_B_array in CpuGemmAssemblyDispatch) However this second optimization depends on how the underlying gemm methods (the fall back path: CpuGemmMatrixMultiplyKernel or the assembly path: CpuGemmAssemblyDispatch) chooses to fuse the transpose. Therefore, this patch moves the transpose down from CpuGemmConv2d, to the individual gemm operators where the fusion decision needs to be made, by passing an extra "transpose_b" flag to CpuGemm New transpose_b flag in different scopes (they are all the same, but with different names because pretranspose_b has a different meaning in GemmAssemblyDispatch): GEMMInfo::pretranspose_B -> AsmGemmInfo::transpose_b New auxilliary tensors holding the transposed b result: - CpuGemm optimized path: CpuGemmAssemblyDispatch::PrePretransposedB - CpuGemm fallback path: CpuGemm::PreTransposedRHS Note that this patch does not yet have the second optimization (COMPMID-6595), but it prepares for it. Relates to COMPMID-6595 Resolves COMPMID-6499 Change-Id: I999a2da9da4b2b15369a3cc06d7872c86e0190ea Signed-off-by: SiCong Li <sicong.li@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10526 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Anitha Raj <Anitha.Raj@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-10-02Optimize CL and Neon Winograd testsGunes Bayir
Several test optimizations have been introduced into Winograd tests for Gpu and Cpu backends. The testing strategy has been detailed as a comment header in the test design files. In summary - Very large shapes in the nightly are made smaller - If the underlying kernel is the same for different data types, we only need to stress some key aspects of the kernels (e.g. read/write lengths in case of fp32/fp16). - In case the underlying kernel is the same (OpenCL), Fp16 is tested on a subset of the shapes - In Cpu, there is no need to test every combination for both NCHW and NHWC as we just permute the inputs and use NHWC kernels anyways - All activations does not need to be tested for each and every shape Resolves: COMPMID-6464 Change-Id: Ie25fded85c65b9c7386dc21b23f9b695b1e77b07 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10393 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-09-28Apply clang-format on repositoryFelix Thomasmathibalan
Code is formatted as per a revised clang format configuration file(not part of this delivery). Version 14.0.6 is used. Exclusion List: - files with .cl extension - files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...) And the following directories - compute_kernel_writer/validation/ - tests/ - include/ - src/core/NEON/kernels/convolution/ - src/core/NEON/kernels/arm_gemm/ - src/core/NEON/kernels/arm_conv/ - data/ There will be a follow up for formatting of .cl files and the files under tests/ and compute_kernel_writer/validation/. Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
2023-09-20Fix the validation issue in AddMulAdd fused kernelGunes Bayir
Resolves: COMPMID-6558 Change-Id: I015d504aaa9b8a1a232b01e49ab373d415ea1de9 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10340 Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Reviewed-by: TeresaARM <teresa.charlinreyes@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-09-15Remove deprecated support for BF16 in CpuCastAdnan AlSinan
Resolves : [COMPMID-6212] Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I29bbd9a3d96af462faf7f0ee13b9849f75e05356 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10319 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
2023-09-15Fix include dependencies for mass reformatting patchGunes Bayir
This patch fixes some include dependencies in certain files that caused build failures in https://review.mlplatform.org/c/ml/ComputeLibrary/+/10287. It also circumvents some clang-format glitches. Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I8e9d3307edd2d1afd17c685c9bc9429624130e5a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10313 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: <felixjohnny.thomasmathibalan@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-09-04Remove legacy PostOps codeJakub Sujak
PostOps was the experimental interface for Dynamic Fusion. It is now replaced by the new Dynamic Fusion interface with code generation using the Compute Kernel Writer. Resolves: COMPMID-6190 Change-Id: I813b48facef2fd6f3aee332588886b4f9b3d33d8 Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10219 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>
2023-08-23Update CpuGemmConv2d and CpuFlatten to use CpuReshape operatorAnitha Raj
- Following CpuReshapeKernel Optimizations, update the CpuGemmConv2D and CpuFlatten to use CpuReshape operator instead of CpuReshapeKernel - Minor changes to comment in NEReorgLayerKernel.h Resolves COMPMID-6504 Signed-off-by: Anitha Raj <anitha.raj@arm.com> Change-Id: Ib6ee1fdc313d91249f9fe41c81e73324031c1ff4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10186 Reviewed-by: Jakub Sujak <jakub.sujak@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>
2023-08-22Optimize CpuReshapeKernelAnitha Raj
Resolves COMPMID-5279 Change-Id: Id9b007eed62c200702bbfcc83b94dab7b5de1714 Signed-off-by: Anitha Raj <anitha.raj@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9962 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-08-17Fix various static check issuesViet-Hoa Do
Resolves: COMPMID-6495 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I916829222a6211fa096a833a2afc5fab5eb34ea4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10143 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-08-07Document the Conv2D heuristicGian Marco Iodice
- Add a new section in the documentation to describe how the conv2D heuristic works on Arm® Cortex®-based CPUs and Arm® Mali™-based GPUs - Add CKW_UNUSED in compute_kernel_writer/src/cl/CLTile.cpp to avoid the compilation error due to an unused variable - Remove FFT from the list of algorithms to be selected by the CPU Conv2d heuristic. Resolves COMPMID-6163 Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Change-Id: I51384d7749451b2562642683e8b2429a355166bb Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10065 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-07-28Retain back-compatibility for arm_compute/core/Types.hSiCong Li
* Some symbols have been moved from core/Types.h. This patch retains back compatibility so that the user can still include this header for those symbols * A new header core/CoreTypes.h is created to avoid circular dependency. This header includes essential small types that are used across functions * Move all function info types into function_info folder for easier tracking Resolves COMPMID-6330 Related to https://review.mlplatform.org/c/ml/ComputeLibrary/+/9757 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: I4739175c2d4d184a9bc8e28b881b497fab03ca60 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9979 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-07-19Add support for input S64/U64 in CpuCastKernelPablo Marquez Tello
* The kernel now supports the following conversions: S64 -> F32 U64 -> F32 * Resolves MLCE-1089 Change-Id: I277cf58b78d919fde25947520d2056e1412c7f82 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9935 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-07-10Do not include headers necessary for logging when logging is disabledMatthew Bentham
Speeds up compilation by 30% for some files when logging is disabled. Signed-off-by: Matthew Bentham <Matthew.Bentham@arm.com> Change-Id: Ia479bd50a80616a34e33ead13db8558f8dbaa1aa Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/534480 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9880 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-07-04Depthwise channel pre-multiplicationMichael Tyler
Resolves: COMPMID-6337 Change-Id: Ie9097b3f56e8071426c621386a5988bd7f7e8ef2 Signed-off-by: Michael Tyler <michael.tyler@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9852 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-06-23Address the issues with the ACL coverage pipeline failures related to matmul.Renato Arantes
Signed-off-by: Renato Arantes <renato.arantes@arm.com> Change-Id: I98de659d1289c930e366727d4799f0dacc8121ab Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9782 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-06-16Add Fused Activation to OpenCL MatMulMohammed Suhail Munshi
- Added fused activation to MatMul function interface - Added fused activation to CL backend - Includes tests for supported Activation Functions in MatMul Resolves: [COMPMID-6192] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Ie103212b600b60699eaf6a6394d609e6e1f5aba6 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/522465 Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9714 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-06-15Break up Utils.h a bit to reduce unused code being included everywhereMatthew Bentham
Move some maths-related things from Utils.h to new Math.h header in utils/math. Move some routines used for Tensor shape validation to Validate.h Change-Id: I8ce89fe03ec3ae1b61d1a80c282b8b91eea0cfb3 Signed-off-by: Matthew Bentham <Matthew.Bentham@arm.com> Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/524783 Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Tested-by: Viet-Hoa Do <viet-hoa.do@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9743 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-06-15Break up arm_compute/core/Types.h a bitMatthew Bentham
Split some of the larger types with inlined code into their own header files, so that the implementation of them needn't be included everywhere. Change-Id: Id3ec2d42efbd33cedb55705a5a24e1b90c8b7a01 Signed-off-by: Matthew Bentham <Matthew.Bentham@arm.com> Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/524782 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9757 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-05-10Re-enable dyanmic weights in Neon™ depthwise convolutionRamy Elgammal
- Call Neon™ depthwise convolution validation inside in its configure() method. Resolves: COMPMID-6188 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Change-Id: Ib2ae4d995ff2bbc92ce4496d4ab93cf09113e3e9 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9594 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-05-05Connect CLMatMul function to quantized kernels and resolve NE BatchMatMul ↵Jakub Sujak
int_8 failures * Adapt the CLMatMul function and ClMatMul operator to use quantized kernels. * Add function-level tests. Resolves: COMPMID-5929 and COMPMID-5811 Change-Id: I5348cdcf07b8074c138e04dfef0a73399377accd Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9575 Reviewed-by: Mohmun02 <MohammedSuhail.Munshi@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-05-05Disable dynamic weights in unsupported operatorsViet-Hoa Do
Resolves: COMPMID-6185 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Icfd9d177083ecdf41dc13e5b2ae982ff67492f8a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9577 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> 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>
2023-05-03Fix im2col for fast-maths mode with padding.Renato Arantes
Following the investigation proposed by ONCPUML-1193, padding is implemented in im2col when the input channel is not a multiple of blocks requested by the weight format. Partially resolves: ONCPUML-1193 Signed-off-by: Renato Arantes <renato.arantes@arm.com> Change-Id: I350c7a1b2dcae63f8d94f5b6f1f86e948eab1f09 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9508 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-05-03Fix CPU MatMul broadcast detectionViet-Hoa Do
Resolves: COMPMID-6155 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Ie651be65404b0b737464d7a79ebcc58475863ba0 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9555 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>
2023-05-02Fix fully connected and matmul mismatchesViet-Hoa Do
* There is an issue with quantized fully connected and matmul when the lower bound of bounded ReLU is negative. * Use int32_t for the calculation of min/max quantized value rather than PixelValue to avoid this issue. Partially resolves: COMPMID-5996 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I7b22e9d56a2441fc6a4c5c4e627f57d6e00d6ff1 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9502 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-04-26Integrate multi-threaded pretranspose_B_arraySiCong Li
This is required for the case where rhs (B) is dynamic and needs to be pretransposed in every run. In a multi-threaded setting, this means the previously single-threaded pretranspose_B_array would become the bottleneck Resolves COMPMID-5896 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: Id508c46992188a0f76a505152931d4955d04c16d Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9455 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-04-19Add quantized support for CPU MatMulViet-Hoa Do
Resolves: COMPMID-5899 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I89d96e292c3492ba9b1900a3e5683f9dcd11dfc6 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9440 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>
2023-04-14Fix dynamic weights for CPU connected layerViet-Hoa Do
Resolves: COMPMID-5995 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I707b8918bebee7e70d4de5207ef555c806e7a305 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9405 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-04-13Implement MatMul Function and Operator with Floating Point support for CPUMohammed Suhail Munshi
- Implements MatMul function and operator for floating point datatype FP16/FP32 - Includes support for transposing dynamic tensors prior to matrix multiplication. - Adds tests for 2D/3D/4D+ tensors in MatMul with F32/F16 datatype (with all combinations of transposed/not-transposed tensors) - Updates fixture to allow for testing fused activation in MatMul - Adds tests for matmul with and without fused activation Resolved: [COMPMID-5898] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Iefa84b26dd723c9a51e6c3f91023152c6c31ace2 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9411 Reviewed-by: SiCong Li <sicong.li@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-03-21Add dynamic weights for CPU fully connected layerViet-Hoa Do
Resolves: COMPMID-5917 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I073067b490f2a1b96b81a037ea431c9a2e5c7503 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9322 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>
2023-03-13[ONCPUML-1174] Allow src/weights mismatch for fixed formatJonathan Deakin
Without this, we have to pass in weights to be NHWC, even if they are in fact blocked/interleaved for consumption by a fixed format kernel. Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com> Change-Id: I9ee8720a21a16b17816dbecf6308e1668ddda59c Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9285 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-03-03NEGEMMLowpMatrixMultiplyCore should be configured for optimized int8 kernel.Ethan Doe
Currently the validation routine incorrectly prevents optimized INT8 Gemm kernel from being used if the input is QASYMM8 and output type is S32. This change allows QASYMM8 input and S32 output types to leverage optimized kernel. Signed-off-by: Ethan Doe <yidoe@amazon.com> Change-Id: I65b060f522795db07d6d4df86fb7c6ddd1c626d4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9250 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-26 12:11:04 +0000