aboutsummaryrefslogtreecommitdiff
path: root/src
AgeCommit message (Collapse)Author
2024-03-27Added new NEON fixed format fast math mode hybrid kernel with maximum height ↵Milos Puzovic
of 6 for accumulation and updated heuristics Change-Id: Ib52ea6825e164f4a8b8422eab7991b50af0b0d7c Signed-off-by: Milos Puzovic <milos.puzovic@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11354 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2024-03-25Adds Tests and reference implementation for scatter operator with 1D tensors.Mohammed Suhail Munshi
Resolves: [COMPMID-6890] Change-Id: Ie4a8db24fc6387afa9ddf42b3607e040cdf8df67 Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11339 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>
2024-03-21Add skeleton for CLScatter op, reference and testsMohammed Suhail Munshi
- Adds dataset for tests - Adds skeleton for function, operator, reference and tests Resolves: [COMPMID-6889] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I7e57e8b4577fef6aa7421e672894c249cad6c5fa Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11234 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>
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>
2024-03-18Fix quant. gemv kernel driver by adding set_quantized_bias()Gunes Bayir
arm_gemm fuses the actual bias addition with the output stage in quantized gemm. The output stage, in its very basic form, is: A_offset * B_offset - sum(A_row_i) * B_offset - sum(B_col_j) * A_offset Matrix B is usually constant (e.g. weight matrix in convolutions). Therefore, except the middle term above, the expression is constant across the same output row because the column sums of matrix B are pre-calculated. The bias is also usually constant. When it is, it makes sense to add the bias vector to the above sum and just perform a single addition on top of the output tensor. For this to happen, the column sum computation of B tensor must account for the bias. This is ensured by set_quantized_bias() method in the interface. This function passes the bias pointer and strides to arm_gemm. Gemv_pretransposed does not implement set_quantized_bias() and uses the parent function, which does nothing. Therefore, the bias is not added to the output. This causes tests to fail. Resolves: COMPMID-6928 Change-Id: Iba24fabc65fdc47edb12db6abff2fb47784c0743 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11310 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
2024-03-14arm_gemm: Fix bias handling for sme2 FP16 GEMV.David Mansell
Resolves: COMPMID-6927 Signed-off-by: David Mansell <David.Mansell@arm.com> Change-Id: Ib426fdc11ddbdbd0028d64547f3eaf312ca5fcce Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11301 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@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>
2024-03-12Fix WoA nightly failurePablo Marquez Tello
* Resolves COMPMID-6931 Change-Id: I3ed0c509807e26bddfcd20be71b12ec4cbb5cce6 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11277 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>
2024-03-11Prefer 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>
2024-03-04Disable FP16 on 32 bitPablo Marquez Tello
* Resolves ARMCL-1129 Change-Id: I3e4e08d5ec401a274912c09674ef4a3245d65489 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11242 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>
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>
2024-03-01Set Neon™ as present for WoAPablo Marquez Tello
* This fixes the failure in the unit test CPU/UNIT/Context/CpuCapabilities. * Resolves MLCE-1221 Change-Id: Ib5b3e8a7276939f6644783550caa245ee3f4fe7b Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11235 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
2024-02-22Fix segfault in DWC in WoAPablo Marquez Tello
* Resolves MLCE-1219 Change-Id: If997180ec88c35d6af05a06c8c5ef95681e67c05 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11182 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>
2024-02-22Fix OpenBSD® build failure caused by patch 11144Gunes Bayir
include of alloca.h should be guarded against _WIN64 and __OpenBSD__ Partially Resolves: COMPMID-6595 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I6a52ec129d92e290d033f75baeb4a598669daae0 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11180 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>
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>
2024-02-14Fix compiler errors in cl-clangPablo Marquez Tello
* cl-clang is used to build ACL natively in WoA * Resolves MLCE-1209 Change-Id: I040e84f526f16324138a074badf764ac099090e3 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11126 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>
2024-02-12Fix 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>
2024-02-09Add support for QSYMM8 in ClCastKernelPablo Marquez Tello
* Resolves ARMCL-1123 Change-Id: I4f8432ba41fa50bf787fb068c3672ac06b858bdd Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11117 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>
2024-02-09Remove CKW prototype and Template WriterGunes Bayir
Gpu code in dynamic fusion is now written by stable CKW. We do not need CKW protoype and the older writer implementation, i.e. TemplateWriter. It also removes the need for the flag -DACL_INTERNAL_TEST_CKW_IN_DF to compile and test dynamic fusion operator. Resolves: COMPMID-6715 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I9f9453311e79d9be612bd4754240d832f98503e8 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11116 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>
2024-02-08Fix the bug in GpuTanh operator in dynamic fusionGunes Bayir
Tanh in dynamic fusion is a simple operator with no A and B coefficients, as its public interface implies. Tanh operator follows the TOSA specification. Customization of tanh calculation with a and b can be achieved via fusion as below: out = a * tanh(b *in) --> x = b * in y = tanh(x) out = a * y; Resolves: COMPMID-6873 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I818765192f631ae82c2094b0fc376fb87bae4fa4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11109 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>
2024-02-08Mark GpuSoftmax and GpuReshape as not supportedGunes Bayir
Softmax and Reshape operators are not supported in CKW. This patch marks them as not supported because we're deprecating template writer. Resolves: COMPMID-6872 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: Ied97e5d21297c28be120c62760d33e6e832dd3b8 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11107 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>
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>
2024-02-06arm_gemm: SME: Remove artificial single-thread constraint on quantized int8 ↵David Mansell
kernels. Change-Id: I81b71ecc0d2e776d132091e074798a79b3141bec Signed-off-by: David Mansell <David.Mansell@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11085 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>
2024-02-05Fix 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>
2024-02-01Use the stable CKW API in the GPU dynamic fusion backendGunes Bayir
- Refactor all kernels to work with the CKW stable API - Add support for sub-tile in the op_load/op_store CKW operator - Fix mismatch in resize - Add comments in all kernels written with CKW to help developers understand the structure of the code - Add texture image support in depthwise convolution written with CKW - Add support for different block sizes in depthwise convolution - Remove the use of the dynamic fusion helper functions. - Add support for floor in the op_unary() of CKW Resolves: COMPMID-6708, COMPMID-6743, COMPMID-6530 Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Change-Id: I8104ce4d04a3138a1aeb0b84940e1f1c89e76069 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10914 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2024-01-25arm_gemm: convolution: optimize convolver.hpp.David Mansell
The code in convolver.hpp generates pointers into either the appropriate point in the input activation tensor or the padding buffer for each kernel point of each output point of the convolution. This is done at runtime interspersed with the data transform and matrix multiplication steps. As such, it can have a significant impact on performance, particularly for low input channel counts. This change improves the performance of this code by streamlining the checks for out of range input points (which must be directed to the padding buffer). The previous implementation checked all four borders for every point. The revised code does the checks one at a time, and for any failing check applies the result to as many output points as possible without repeating the other checks. Signed-off-by: David Mansell <David.Mansell@arm.com> Change-Id: I36a4fa114b425c1bcba2be40acf36718522519f5 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11004 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@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>
2024-01-23Fix for unchecked return value detected in Coverity checks.Anitha Raj
Resolves: COMPMID-6753 Signed-off-by: Anitha Raj <anitha.raj@arm.com> Change-Id: I80df0479eb4c7cc2c5380df708844cc9ffdd2aed Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11001 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>
2024-01-23Make GpuWorkloadContext own all tensor info objectsViet-Hoa Do
* The tensor info objects created by calling create_tensor_info is now solely owned by the context object. The user only receives pointers to those objects. - Internally pointers to tensor info objects are used in various places. It's safer for dynamic fusion to manage these objects directly rather than relying on the users. - The validation test is updated to use the modified API. * Make various changes in dynamic fusion API to make it more friendly (e.g. making some of the objects moveable). Partially resolves: COMPMID-6707 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Ifee70e53c05f8e7b72bf9ef123701ff291c5ee80 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10990 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>
2024-01-18Fix divide-by-zero compilation errorViet-Hoa Do
* CONVERT_TO_TENSOR4D_STRUCT_NO_STEP is implemented and used in some CL kernels in the way that causes divide-by-zero issue. - Since the steps are all zeros, the issue might have been ignored by the compiler. Resolves: COMPMID-6795 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I0fb38fc62d63671b8abefa39b3d9b3ca6f49c7fe Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10967 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>
2024-01-17Fix minor issue, clean lut codeMohammed Suhail Munshi
Resolves: [COMPMID-6799] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I47baeeea75f1d03609d1fa1e9a10d2f53d5694f7 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10969 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>
2024-01-12Fix potential threading issue in LUTManagerMohammed Suhail Munshi
- Locks pointer before checking for validity to prevent race condition Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I6872b10d058ee7f3707ba641f44bb6116e26880a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10960 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>
2024-01-12[ONCPUML-1387] Add ACL based reorder for f32 to bf16 data type conversion.Renato Arantes
The reorders supported at the moment are: ab->BA4b4a ab->BA8b4a Co-Authored-By: David Mansell <David.Mansell@arm.com> Change-Id: Ic466465629ce3bcdcee0089e251485b79b60e1f3 Signed-off-by: Renato Arantes <renato.arantes@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10775 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>
2024-01-10Fix compilation error on GCC 13.2Jakub Sujak
Suppress a false positive compiler warning caused by a bug in GCC https://gcc.gnu.org/bugzilla/show_bug.cgi?id=104165 This issue is known to be reproducible in some versions of GCC 11, 12 and 13. Remove a redundant std::move flagged by -Werror=redundant-move Resolves: COMPMID-6777 Change-Id: I782e87b5e3df4c09195e67a37f49d122dc918224 Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10950 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: <felixjohnny.thomasmathibalan@arm.com> Comments-Addressed: <felixjohnny.thomasmathibalan@arm.com> Comments-Addressed: 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>
2023-12-22Fix nightly issue caused by gemm_reshaped_only_rhs_mmul kernelGunes Bayir
The issue appears when this kernel is used by convolution operators because the stride calculations consider only simple matrix multiplication. In conv2d triggered runs, Rhs does not have the same dimension as Lhs and Dst. Also, cases where Lhs and Dst are interpreted as 3d, where their X and Y dimensions (in convolution sense) are collapsed into one. Resolves: COMPMID-6764 Change-Id: If443e6eb8f7a5cca1acc58b37c598122a013e69b Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10913 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-12-22Add Mali™-G720 and Mali™-G620 as GpuTargetsGunes Bayir
This patch adds adds the latest Gpus as Gpu Target and sets up kernel selection heuristics for MatMul to address some nightly issues. Resolves: COMPMID-6766 Change-Id: I29dbb08c5ecfb3fcd63230b0b1675ab557074aca Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10902 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-12-15Fix nightly bug caused by not validation 3d cases for input tensorGunes Bayir
While writing this gemm kernel, code pieces, including validations were adapted from ClGemmMatrixMultiplyReshapedOnlyRhsKernel, and this validation should be about reinterpret_input_as_3d. This reveals a test gap for this kernel. There are currently no tests stressing this condition; but this is not going to be addressed as part of the bug ticket. The corresponding snippet in ClGemmMatrixMultiplyReshapedOnlyRhsKernel is if (gemm_info.reinterpret_input_as_3d) { ARM_COMPUTE_RETURN_ERROR_ON(src0->dimension(1) * src0->dimension(2) != m); } else { ARM_COMPUTE_RETURN_ERROR_ON(src0->dimension(1) != m); } Resolves: COMPMID-6757 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I4363effcaf2b43ff3674a3443058384338fb9714 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10891 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
2023-12-15Revert "Fix nightly bug caused by wrong validation in Gemm mmul kernel"Gunes Bayir
This reverts commit 270576a9fbeeda5210483931388e62f9a1059dd9. Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: Ia4e965156af46a9afd78819e90fd2a033a97fc2b Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10888 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-12-14Fix validation error in CL generate proposals kernelGunes Bayir
This fix modifies some of the conversions done in the generate proposals kernel that causes DDK issues while compiling the kernel. The issues are mostly related to conversion from i64 to fp16, and it doesn't affect fp32. Firstly, type identifier size_t is converted into unsigned int. But, this alone was compiling but causing mismatches, even in older devices, where it was passing before. Therefore, the fp16 conversion delayed until vector construction where the integers are now converted to fp32, and then fp16. This, although may not be ideal, seems like the best solution. Resolves: COMPMID-6756 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: Iee61216c908fe51431985b80c3653fc32add4741 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10879 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-12-13Fix nightly bug caused by wrong validation in Gemm mmul kernelGunes Bayir
While writing this gemm kernel, code pieces, including validations were adapted from ClGemmMatrixMultiplyReshapedOnlyRhsKernel, and this validation should be about reinterpret_input_as_3d, which is not dealt with in this kernel. The mmul kernel only deals with reinterpret_output_as_3d, which is equivalent to depth_output_gemm3d != 0. This reveals a test gap for this kernel. There are currently no tests stressing this condition; but this is not going to be addressed as part of the bug ticket. The corresponding snippet in ClGemmMatrixMultiplyReshapedOnlyRhsKernel is if (gemm_info.reinterpret_input_as_3d) { ARM_COMPUTE_RETURN_ERROR_ON(src0->dimension(1) * src0->dimension(2) != m); } else { ARM_COMPUTE_RETURN_ERROR_ON(src0->dimension(1) != m); } Resolves: COMPMID-6757 Change-Id: I73b203594b22098a5374c1fac6969ee769969901 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10874 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: 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>
2023-12-08Fix validation error in graph_ssd_mobilenetGunes Bayir
The graph example has fixed quantization information given for certain layers, and some of the offsets exceed the 8-bit range for Int8 data type. This shouldn't have been the case and the offsets should respect the 8-bit quantization specification laid out here: https://www.tensorflow.org/lite/performance/quantization_spec However, the mechanism added in the helper function introduces robustness in case of such irregularities with little/no cost; and therefore added as a fix. Resolves: COMPMID-6748 Change-Id: If39bf323382f109fa100ee2b87ce63cc7bc89759 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10858 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>
2023-12-08Fix unit tests failing in CL/UNIT/TensorAllocatorGunes Bayir
The function pointer for clImportMemoryARM should be loaded in a portable way as recommended by Khronos® as outlined here: https://registry.khronos.org/OpenCL/specs/3.0-unified/html/OpenCL_Ext.html#getting-opencl-api-extension-function-pointers using clGetExtensionFunctionAddressForPlatform() call. All extensions should ideally be loaded using the above mentioned function. Resolves: COMPMID-6732 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I482b6bde721267d5e8c08301e5780d28a9c5ba85 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10852 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>