aboutsummaryrefslogtreecommitdiff
path: root/src
AgeCommit message (Collapse)Author
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>
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>
2023-11-28Changes to enable FP16 in armv8a multi_isaPablo Marquez Tello
* This is the initial patch to start working on enabling fp16 in all multi_isa builds. More changes are required in the way we register the kernels using the macro REGISTER_FP16_NEON. * In this patch we add the capability to build the fp16 files in listed in filelist.json with the correct arch option to enable FP16 * This patch is required towards building an universal multi_isa binary where fp16 is enable. * Enable REGISTER_FP16_NEON macro for all builds by removing __ARM_FEATURE_FP16_VECTOR_ARITHMETIC guard from the macro definition. The macro has to be used across all types of builds. Change-Id: I99f4c273f6ee04cad3c097e5e374200f48568fa9 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10682 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>
2023-11-27BatchNorm 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>
2023-11-15Fix device issue with CL softmaxViet-Hoa Do
* Performing the second pass in reverse order doesn't seem to work reliably in some specific devices. This patch introduces another approach to workaround the device issue. Resolves: COMPMID-6669 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I591f05ff06f8439ebe4d32093441ae871a292f4c Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10730 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>
2023-11-14Update comments to suppress doxygen warnings.Anitha Raj
Resolved COMPMID-6367 Signed-off-by: Anitha Raj <anitha.raj@arm.com> Change-Id: I96f244811a81a4e278f0c5e47d5014229cad3a25 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10727 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>
2023-11-10Fix 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>
2023-11-09Remove duplicate definitions of BF16 fixed format kernels.David Mansell
Change-Id: Ie68b0a19040cc6b5bf47fca406989f39aa8d7b81 Signed-off-by: David Mansell <David.Mansell@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10687 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>
2023-11-09Pooling 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>
2023-11-07Update heuristic for MatMul Native U8Gian Marco Iodice
Resolves COMPMID-6479 Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Change-Id: I13aa0ef944a75ba8b5e4df183d52df57b9aba90f Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10659 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>
2023-11-01Add support for Arm® Cortex®-A520 and Arm® Cortex®-R82Viet-Hoa Do
Resolves: COMPMID-6599 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Id91185871f0dc30c08c7c38379acd5a3c1056473 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10575 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>
2023-11-01Fix compilation error with clang and multi-isaViet-Hoa Do
* Fix SVE header being included in non-SVE file. Resolves: COMPMID-6613 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Ic7f662a239b761b83e67e11b6cc03f7d5f5cd051 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10573 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>
2023-10-31[GPU] Update Reverse layer to allow negative axis and reversed axis orderAdnan AlSinan
- Adds option to use negative axis and inverted axis. - Adds validation tests for the above. Resolves COMPMID-6459 Change-Id: I88afd845d078f92c82ec8529ce7241fccd4c417e Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10523 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-10-31Extend CKW MatMul with nt_tAdnan AlSinan
- Add the kernel variant: (nt_t) to GpuCKWMatMul. - Extend CKW MatMul validation test with nt_t. - Fixes a bug in CKW where z-dim = 1. Resolves: COMPMID-6435 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I4c5e8791e55f21ffff3c11eca7802c51a4259977 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10525 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-10-31Fix SVE kernel using SVE2 instructionViet-Hoa Do
Resolves: COMPMID-6493 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I038d91ba266e1e8bf124336bcd272ec77e92038c Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10490 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>
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-19 05:32:02 +0000