aboutsummaryrefslogtreecommitdiff
path: root/src/cpu
AgeCommit message (Collapse)Author
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>
2024-03-20Make Cpu/Gpu/Ref scalar/vectoral S32 division consistentGunes Bayir
- Neon(TM) implementation converts integers to float and performs the division because there is no vector integer division instructions. However, leftover loop still uses integer division, which makes results inconsistent depending on where we are in the tensor. - SVE path does it in integer domain. - OpenCL(TM) does it similar to Neon(TM) vector path. - Reference implementation does it in integer domain. These differences cause intermittent mismatches. This patch ensures all follow the same logic. On the other hand, the provided Neon(TM) implementation is faster than the Fp32 converted version. Resolves: COMPMID-6925 Change-Id: Ia12606d57f40a7d331b9b698f87fd4321496b275 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11316 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>
2024-03-19Fix overflow in NEMeanStdDevNormalizationKernelPablo Marquez Tello
* Perform final sum in fp32 to avoid overflow * Resolves ARMCL-1128 Change-Id: I89799baf81045697f7bc44017fcb6a440635caff Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11311 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>
2024-03-14Fix validation in pool2d assembly wrapperPablo Marquez Tello
* Validate output shape in CpuPool2dAssemblyWrapperKernel * Resolves ARMCL-625 Change-Id: I4fd91c1b15ecb17efc39fd3e82a92210e4f182b2 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11290 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>
2024-03-12Optimize 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>
2024-02-05Fix leftover cols in CpuGemmLowpMatrixBReductionKernelJonathan Deakin
CpuGemmLowpMatrixBReductionKernel::run_internal randomly segfaults because it reads out of bounds with vloadq. This doesn't trigger with the unit tests because the read isn't out of bounds for the process, but it can be seen clearly by running the following in debug mode ./examples/neon_gemm_qasymm8 1 1 1 The vloadq at src/cpu/kernels/CpuGemmLowpMatrixReductionKernel.cpp:353 accesses a quadword even though the input is a single byte. relates to: ONCPUML-1444 MLINFSW-439 COMPMID-6844 Change-Id: I2ae5260c9f38d6d8149a6bcd5dc146b911209784 Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10966 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>
2024-01-23Fix for Logically dead code detected in Coverity checksAnitha Raj
Resolves: COMPMID-6746 Signed-off-by: Anitha Raj <anitha.raj@arm.com> Change-Id: I96c158820469af3e54dca0c5909c888106eb1940 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11005 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>
2024-01-10Use look up table for fp16 activationMohammed Suhail Munshi
- Enables FP16 lut for logistic activation - Adds LUTManager to re-use lut where appropriate. Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I94667b63b452a8e58a1eb59cb0b5866178954523 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10864 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>
2024-01-04Prevent RELU from being processed thru LUT in INT8Sangwon Ha
- For quantized RELU activation, de-quantization and re-quantization is not required since comparison against the quantization bias is only required. Resolves: COMPMID-6340 Change-Id: I574bd220f3d0d893b7f7c4819a883e2a131f61f4 Signed-off-by: Sangwon Ha <sangwon.ha@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10916 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: <felixjohnny.thomasmathibalan@arm.com> Benchmark: 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>
2023-12-07Optimize CPU depth-to-spaceViet-Hoa Do
Resolves: COMPMID-6622 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Ibac276618bdda125dcbb9c851c547f12739b15b4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10749 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>
2023-12-06Revert "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>
2023-11-27BatchNorm changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Moved NCHW kernels fp16 and fp32 to their corresponding files src/cpu/kernels/fuse_batch_normalization/nchw/neon/fp16.cpp and src/cpu/kernels/fuse_batch_normalization/nchw/neon/fp32.cpp * Changes in filelist.json to include the new fp16 and fp32 files * Moved the template batch_normalization_nchw to impl.h as we need to instantiate it from fp16.cpp and fp32.cpp * Pooling layer: removed the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC that prevented the FP16 kernel execution. * Partially resolves MLCE-1102 Change-Id: Ia8c85e9ffb76c9e387f9ae2685e5df5e52c8dc27 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10777 Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-11-27CpuMul changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Moved fp16 and fp32 to their corresponding files src/cpu/kernels/mul/generic/neon/fp16.cpp and src/cpu/kernels/mul/generic/neon/fp32.cpp * Changes in filelist.json: added a new fp16.cpp file for the float16_t kernels * Partially resolves MLCE-1102 Change-Id: I88f24cf034c11b55ff84644b182ba76c7cb94296 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10778 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@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>
2023-11-16NormalizationLayer changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Moved the template arm_compute::normalize_float to impl.h because we need to instantiate it from both NENormalizationLayerKernel.cpp and src/cpu/kernels/norm_layer/generic/neon/fp16.cpp * Changes in filelist.json: added a new fp16.cpp file for the float16_t kernels * Replaced the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC in NENormalizationLayerKernel by ARM_COMPUTE_ENABLE_FP16 so that the fp16 kernels can be compiled in for multi_isa builds * Moved fp32 kernels to the corresponding file src/cpu/kernels/norm_layer/generic/neon/fp32.cpp * Partially resolves MLCE-1102 Change-Id: I3f2eb2ed0b6c7f68092b17872b85082fbb5f39e2 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10739 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>
2023-11-15Fix 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>
2023-11-09Pooling changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Changes in filelist.json moving fp16 file from common to fp16 attribute * Changes in kernel CpuPool2dAssemblyWrapperKernel, replaced __ARM_FEATURE_FP16_VECTOR_ARITHMETIC by ENABLE_FP16_KERNELS to make sure the fp16 kernels are compiled in for multi_isa=1 * Partially resolves MLCE-1102 Change-Id: I327154ec5b1ddfb9f54d9096f00c35b3e05c678a Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10662 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>
2023-11-09DepthwiseConvolution changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Changes in filelist.json moving fp16 file from common to fp16 attribute * Removed the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC in CpuDepthwiseConv2dAssemblyWrapperKernel to always create the assembly kernel * Partially resolves MLCE-1102 Change-Id: I2f88d5e54a94042cfb3cb4ea0386338a7c444866 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10626 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>
2023-11-08Optimize 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>
2023-10-30DirectConv and Im2Col changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* FP16 kernels must be instantiated in fp16.cpp. * Partially resolves MLCE-1102 Change-Id: Iab9c29dbfd89358f2f663862ff5010c88aeccf8c Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10496 Reviewed-by: Anitha Raj <Anitha.Raj@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-10-20FuseBatchNorm changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* FP16 kernels must be instantiated in fp16.cpp. * Partially resolves MLCE-1102 Change-Id: Ie652203876a0ac12b025e96d20990b6efb21e772 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10477 Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-10-13Fix build error in CpuScalePablo Marquez Tello
* Build error when using data_layout_support=nhwc * Some kernels need to be guarded by ENABLE_NCHW_KERNELS Change-Id: I0414084b458360c7e8d2842f4734c39aad80852e Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10476 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-10-12Scale changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Partially resolves MLCE-1102 Change-Id: If050608e56d75649b8d07757604ae10d6fc4269b Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10461 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-10-10Fix build errorPablo Marquez Tello
* Build error when using data_layout_support=nhwc * Some kernels need to be guarded by ENABLE_NCHW_KERNELS Change-Id: I9fb6cf0e204531f81b0dff3572a1740ba94cde0e Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10460 Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-10-10CpuSubKernel changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* FP16 kernels must be instantiated in fp16.cpp. * Partially resolves MLCE-1102 Change-Id: I497fe0ba6e84493a5072c3e80bbba7ecd5de8095 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10448 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>
2023-10-09Pool2d changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* FP16 kernels must be moved from src/cpu/kernels/pool2d/neon/nchw/all.cpp to src/cpu/kernels/pool2d/neon/fp16.cpp. * In src/cpu/kernels/pool2d/neon/list.h when we declare the kernels we need to remove defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) so that in std::vector<CpuPool2dKernel::PoolingKernel> available_kernels * Partially resolves MLCE-1102 Change-Id: I000380f8eccca17e6219c4f3453980d67a2c9dd8 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10444 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>
2023-10-05Optimize CLTranspose operatorJakub Sujak
* Transpose higher dimensional tensors (>2D) by collapsing higher dimensions into the third dimension thus avoiding multiple dispatches of the CL kernel * Maximize tile size without register spilling Resolves: COMPMID-6448 Change-Id: Iac094b8c428bdf319d9c28a8334cb55d58e2d14b Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10443 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>
2023-10-02Optimize 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>
2023-09-26Re-arrange header inclusion orderFelix Thomasmathibalan
Inclusion order of header is changed as preparatory step for applying clang-format Change-Id: I0c529f896ba802dfc6f30a573cdc9d9a24f3081c Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10379 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-09-26Select changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * fp16.cpp needs to use the template select_op() which had to be moved from impl.cpp to fp16.cpp * Partially resolves MLCE-1102 Change-Id: Ic9e73e121482fcc5e4fcbe8ae1ecd23649cbd3d1 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10359 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
2023-09-26Maxunpooling changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * fp16.cpp needs to use the template max_unpooling() which had to be moved from impl.cpp to impl.h * Partially resolves MLCE-1102 Change-Id: Iabf9a9ba9d2441032f931f33aad97acc3e332575 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10362 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
2023-09-21L2Norm changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * fp16.cpp needs to use the template l2_normalize_x() and l2_normalize_yz which had to be moved from impl.cpp to impl.h * Removed impl.cpp * Partially resolves MLCE-1102 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Change-Id: Id00a823730108293fc712295a178dad80588af30 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10344 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-09-21Gemm changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * fp16.cpp needs to use the templates vector_matrix_multiply_f16() and matrix_matrix_multiply_f16 which had to be moved from impl.cpp to fp16.cpp * Partially resolves MLCE-1102 Change-Id: Ic87440797d6f1653c815ab6565972206f5afd0ad Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10345 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@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>
2023-09-15GenerateProposals changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * fp16.cpp needs to use the template compute_all_anchors() that had to be moved from impl.cpp to impl.h * Partially resolves MLCE-1102 Change-Id: Iaff6da32d0b9789ef87ba3f95bef99343612bd01 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10309 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-09-15Fuse batch normalization changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * fp16.cpp needs to use the template fused_batch_normalization_dwc_nhwc() that had to be moved from impl.cpp to impl.h * Removed impl.cpp * Partially resolves MLCE-1102 Change-Id: Idaaa113c71729e32e565acf5fb5694c76c36d76d Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10308 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@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>
2023-09-13Softmax changes to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * fp16.cpp needs to use various templates that had to be moved from impl.cpp to impl.h * Partially resolves MLCE-1102 Change-Id: I2e5e68fbcf5279de1ffc1be4def4f96ed05593e9 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10224 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-09-13Changes to InstanceNrom to enable fp16 in armv8a multi_isa buildsPablo Marquez Tello
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs to be moved to an fp16.cpp file to allow compilation with -march=armv8.2-a+fp16 * Partially resolves MLCE-1102 Change-Id: If53ff1927948b3ad7c9e3c9347bc2af38764e342 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10243 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>
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-11 19:50:14 +0000