* Add SME F16 GEMV micro-kernel.

* The GEMV micro-kernel uses instructions compatible with FEAT_SME.

* The GEMV micro-kernel is designed to reuse the same RHS packing functions as the SME F16 GEMM.

This new GEMV micro-kernel is compatible with FEAT_SME but not FEAT_SME2 requirement. By using pairs of `FMLALB` and `FMLALT` instructions, we can reuse the existing RHS data format of the GEMM operation where `kr=2` thus eliminating the need for a specialized packing function for the GEMV operation.

Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>

Approved-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>

This SME1 GEMV kernel computes a 1x8VL block and is designed to work with the same RHS packing function as the SME1 GEMM.

Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>

Reviewed-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

Nikhil Gupta authored Jul 08, 2025 and Anton Bondarenko committed Jul 08, 2025

- Matrix multiplication (MxN) Micro-kernels of QAI8DXP LHS and QSI4CXP
  RHS with BF16 output, optimized for FEAT_I8MM.
- Matrix multiplication (1xN) Micro-kernels of QAI8DXP LHS and QSI4CXP
  RHS with BF16 output, optimized for FEAT_DotProd.

Signed-off-by: Nikhil Gupta <nikhil.gupta2@arm.com>
Signed-off-by: Evie Wright <evie.wright@arm.com>

Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Evie Wright <evie.wright@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

Signed-off-by: Anton Bondarenko <anton.bondarenko@arm.com>

Approved-by: Dan Johansson <dan.johansson@arm.com>

Evie Wright authored Jun 26, 2025 and Viet-Hoa Do committed Jun 26, 2025

Improves performance of ‘kai_rhs_pack_nxk_qsi4c32pnrx8_qsu4c32s1s0_neon’ by vectorizing row summation

Signed-off-by: Evie Wright <evie.wright@arm.com>

Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

Evie Wright authored Jun 25, 2025 and Viet-Hoa Do committed Jun 25, 2025

Signed-off-by: Evie Wright <evie.wright@arm.com>

Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Approved-by: Viet-Hoa Do <viet-hoa.do@arm.com>

Signed-off-by: Anton Bondarenko <anton.bondarenko@arm.com>

Approved-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>

Anitha Raj authored Jun 24, 2025 and Anton Bondarenko committed Jun 24, 2025

* Matrix multiplication (1xN) micro-kernels to compute the matrix multiplication of dynamically quantized symmetric signed 8-bit integer with per-block quantization (QSI8D32) LHS matrix and quantized asymmetric 4-bit signed integer with per-block quantization (QAI4C32) RHS matrix and the accumulation of the result into a single-precision (F32) and half-precision (F16) output, optimized for FEAT_DotProd and packing parameter kr = 8.

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

Adds F16 GEMM micro-kernel using SME1 MOPA instruction and 2VL x 2VL block size. This SME1 kernel is compatible with existing SME F16 LHS and RHS packing functions.

Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>

Approved-by: Viet-Hoa Do <viet-hoa.do@arm.com>

* Add GEMM F32 kernel using SME1 MOPA with block size 2VLx2VL.
* Add tests for the newly added kernel.
* Add CI job to run the kernel on FVP with SME1 and without SME2.

Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>

Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

Signed-off-by: Emil Ohlsson <emil.ohlsson@arm.com>

Approved-by: Jakub Sujak <jakub.sujak@arm.com>

Anitha Raj authored Jun 13, 2025 and Emil Ohlsson committed Jun 13, 2025

* Matrix multiplication (MxN) micro-kernels to compute the matrix multiplication of dynamically quantized symmetric signed 8-bit integer with per-block quantization (QSI8D32) LHS matrix and quantized asymmetric 4-bit signed integer with per-block quantization (QAI4C32) RHS matrix and the accumulation of the result into a single-precision (F32) output, optimized for FEAT_DotProd

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Reviewed-by: Anitha Raj <anitha.raj@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Move the assembly blocks of the following kernels into their own files:
- rhs_pack_kxn_f32p2vlx1biasf32_f32_f32_sme
- lhs_pack_f32p2vlx1_f32_sme
- matmul_clamp_f32_f32_f32p16vlx1b_1x16vl_sme2_mla
- matmul_clamp_f32_f32_f32p2vlx1b_1x16vl_sme2_mla
- matmul_clamp_f32_f32p2vlx1_f32p2vlx1biasf32_sme2_mopa

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Move the assembly blocks of the following kernels into their own files:
- lhs_pack_x16p2vlx2_x16_sme
- rhs_pack_kxn_x16p2vlx2b_x16_x16_sme
- matmul_clamp_f16_f16p2vlx2_f16p2vlx2_2vlx2vl_sme2_mopa
- matmul_clamp_f16_f16_f16p2vlx2b_1x16vl_sme2_dot

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Move the assembly blocks of the following kernels into their own files:
- lhs_pack_x8p2vlx4_x8_sme
- rhs_pack_kxn_qsi8cxp2vlx4sb_qs8cx_f32_i32_sme
- matmul_clamp_qai8_qai8_qsi8cxp2vlx4sb_1x16vl_sme2_dot
- matmul_clamp_qai8_qai8p2vlx4_qsi8cxpsb2vlx4_2vlx2vl_sme2_mopa

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Fix issue in kernels
- matmul_clamp_f32_f32_f32p16vlx1b_1x16vl_sme2_mla
- matmul_clamp_f32_f32_f32p2vlx1b_1x16vl_sme2_mla

where kai_get_m_step returns the incorrect value.

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Evie Wright authored Jun 05, 2025 and Anton Bondarenko committed Jun 05, 2025

Optimize the transposed RHS packing function for matmul_clamp_f32_qai8dxp_qsi4c32p using advanced SIMD, for kr / sr = 8

Signed-off-by: Evie Wright <evie.wright@arm.com>

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Reviewed-by: Anitha Raj <anitha.raj@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Evie Wright <evie.wright@arm.com>
Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

This change adds MSVC support for the imatmul kernels. As a result, they
are also aligned, which results in some additional diffs.

Signed-off-by: Emil Ohlsson <emil.ohlsson@arm.com>

Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

Anitha Raj authored Jun 04, 2025 and Jakub Sujak committed Jun 04, 2025

* Matrix multiplication (MxN) micro-kernels to compute the matrix multiplication of dynamically quantized symmetric signed 8-bit integer with per-block quantization (QSI8D32) LHS matrix and quantized asymmetric 4-bit signed integer with per-block quantization (QAI4C32) RHS matrix and the accumulation of the result into a half-precision (F16) output, optimized for FEAT_DotProd.

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Approved-by: Jakub Sujak <jakub.sujak@arm.com>

- Example demonstrates creating an indirect buffer using a Conv2D input tensor
- Example demonstrates indirect buffer usage with imatmul kernels.

Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>

Reviewed-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Suhail M <mohammedsuhail.munshi@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Signed-off-by: Emil Ohlsson <emil.ohlsson@arm.com>

Approved-by: Viet-Hoa Do <viet-hoa.do@arm.com>

Anitha Raj authored May 30, 2025 and Felix Johnny Thomasmathibalan committed May 30, 2025

* Micro-kernels (1xN) to compute the matrix multiplication of dynamically quantized asymmetric 8-bit integer with per-channel quantization (QAI8DX) LHS matrix and quantized symmetric 8-bit integer with per-channel quantization (QSI8CX) RHS matrix and the accumulation of the result into a single-precision (F32) output, optimized for SME2 technology.
*  Micro-kernels (MxN) to compute the matrix multiplication of dynamically quantized asymmetric 8-bit integer with per-channel quantization (QAI8DX) LHS matrix and quantized symmetric 8-bit integer with per-channel quantization (QSI8CX) RHS matrix and the accumulation of the result into a single-precision (F32) output, optimized for SME2 technology.

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Approved-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>

Update all version indicators to 1.8.0.

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Jakub Sujak <jakub.sujak@arm.com>

Suhail M authored Apr 24, 2025 and Jakub Sujak committed Apr 24, 2025

- Adds packing and matmul kernels for FP32 SME Indirect GEMM
- Adds tests for Indirect Gemm with FP32 inputs/outputs.

Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>

Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Mohammed Suhail Munshi <mohammedsuhail.munshi@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Jens Elofsson authored Apr 24, 2025 and Jakub Sujak committed Apr 24, 2025

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>
Approved-by: Jakub Sujak <jakub.sujak@arm.com>

This change introduces three new kernels
* `kai_lhs_imatmul_pack_x16p2vlx2_x16p_sme`
* `kai_rhs_imatmul_pack_kxn_x16p2vlx2b_x16_x16_sme`
* `kai_imatmul_clamp_f16_f16p2vlx2_f16p2vlx2_2vlx2vl_sme2_mopa`

These are used for indirect matmul, for 16-bit floating point data.

This change also adds unit testing for the FP16 imatmul kernels. The
code is written in a type agnostic manner, as to easily allow testing
for other data types with very low effort. This required the addition of
non-templated `read`/`write` functions, as to allow runtime-generic
access.

Signed-off-by: Emil Ohlsson <emil.ohlsson@arm.com>

Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

Evie Wright authored Apr 15, 2025 and Jakub Sujak committed Apr 15, 2025

Signed-off-by: Evie Wright <evie.wright@arm.com>

Approved-by: Jakub Sujak <jakub.sujak@arm.com>

Update all version indicators to 1.7.0.

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Anitha Raj authored Apr 11, 2025 and Viet-Hoa Do committed Apr 11, 2025

Micro-kernels to compute the matrix multiplication of dynamically quantized asymmetric signed 8-bit integer with per-channel quantization (QAI8DX) LHS matrix and quantized symmetric 4-bit signed integer with per-channel quantization (QSI4CX) RHS matrix and the accumulation of the result into a half-precision (F16):

Matrix multiplication (MxN) Micro-kernels of QAI8DX LHS and QSI4CX RHS with F16 output, optimized for FEAT_I8MM and FEAT_DotProd. 
Matrix multiplication (1xN) Micro-kernels of QAI8DX LHS and QSI4CX RHS with F16 output, optimized for FEAT_DotProd.

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Signed-off-by: Evie Wright <evie.wright@arm.com>

Approved-by: Viet-Hoa Do <viet-hoa.do@arm.com>

Anitha Raj authored Apr 09, 2025 and Anton Bondarenko committed Apr 09, 2025

Micro-kernels to compute the matrix multiplication of dynamically quantized symmetric signed 8-bit integer with per-block quantization (QSI8D32) LHS matrix and quantized asymmetric 4-bit signed integer with per-block quantization (QAI4C32) RHS matrix and the accumulation of the result into a single-precision (F32) and half-precision (F16) output:

- Matrix multiplication (MxN) Micro-kernels of QSI8D32 LHS and QAI4C32 RHS with F32 output, optimized for FEAT_I8MM.
- Matrix multiplication (1xN) Micro-kernels of QSI8D32 LHS and QAI4C32 RHS with F32 output, optimized for FEAT_DotProd.
- Matrix multiplication (MxN) Micro-kernels of QSI8D32 LHS and QAI4C32 RHS with F16 output, optimized for FEAT_I8MM.
- Matrix multiplication (1xN) Micro-kernels of QSI8D32 LHS and QAI4C32 RHS with F16 output, optimized for FEAT_DotProd.

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Anitha Raj <anitha.raj@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Approved-by: Anton Bondarenko <anton.bondarenko@arm.com>

This change introduces three new kernels:

* kai_imatmul_clamp_qai8_qai8p2vlx4_qsi8cxpsb2vlx4_2vlx2vl_sme2_mopa
* kai_lhs_imatmul_pack_x8p2vlx4_x8p_sme
* kai_rhs_imatmul_pack_kxn_qsi8cxp2vlx4sb_qs8cx_f32_i32_sme

These kernels are used for _indirect matmul_. The big difference between
these kernels and matmul kernels is that the LHS packing kernel takes an
indirection buffer where each pointer refers to a chunk in K dimension.
The pointers are laid out in a packed manner, where instead of being in
row major order, a column of `get_m_step` chunk pointers are placed
linearly in indirection buffer.

In addition to the kernels themselves, the
`matmul_clamp_qai8_qai8p_qsi8cxp_test.cpp` is extended to perform
testing of these new kernels. The testing flow for these new kernels is
a bit different, in that the packing kernels themselves are not directly
tested, instead only end-to-end flow is tested.

Signed-off-by: Emil Ohlsson <emil.ohlsson@arm.com>
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>

Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Anton Bondarenko <anton.bondarenko@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Jakub Sujak <jakub.sujak@arm.com>

Update all version indicators to 1.6.0.

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Jakub Sujak <jakub.sujak@arm.com>

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Jakub Sujak <jakub.sujak@arm.com>

Dan Johansson authored Mar 26, 2025 and Emil Ohlsson committed Mar 26, 2025

Optimizes this RHS packing by vectorizing the XOR operation. This is done
for segment lenghts of 4 or 8 bytes. The unoptimized path is used for
any other segment length.

Signed-off-by: Dan Johansson <dan.johansson@arm.com>

Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

* Alias the KleidiAI target for consistent linking to KleidiAI with `KleidiAI::kleidiai`.
* Add install instructions for the KleidiAI library target and its public headers.
* Export the KleidiAI target so that projects may use the imported target with `find_package()`.

Usage:

Install KleidiAI:
```
cmake -S . -B build
cmake --build build
cmake --install build
```

Once installed, KleidiAI can be imported and linked to using `find_package()`.

```
find_package(KleidiAI CONFIG REQUIRED)
target_link_libraries(my_framework PRIVATE KleidiAI::kleidiai)
```

Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>

Approved-by: Viet-Hoa Do <viet-hoa.do@arm.com>

Jens Elofsson authored Mar 12, 2025 and Emil Ohlsson committed Mar 12, 2025

Update all version indicators to 1.5.0.

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>

Anitha Raj authored Mar 12, 2025 and Emil Ohlsson committed Mar 12, 2025

Fix for reading LHS scale values from in kai_matmul_clamp_f32_qsi8d32p1vlx4_qsi4c32p4vlx4_1vlx4vl_sme2_mopa

Fix the out-of-bounds read while loading the scale values from LHS packed matrix in \`kai_matmul_clamp_f32_qsi8d32p1vlx4_qsi4c32p4vlx4_1vlx4vl_sme2_mopa\` by updating the predicate

Resolves: KLEIDIAI-507

Signed-off-by: Anitha Raj <anitha.raj@arm.com>

Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: Emil Ohlsson <emil.ohlsson@arm.com>
Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Signed-off-by: Jens Elofsson <jens.elofsson@arm.com>

Approved-by: Emil Ohlsson <emil.ohlsson@arm.com>

Jakub Sujak authored Feb 24, 2025 and Felix Johnny Thomasmathibalan committed Feb 24, 2025

* Refactor the benchmark tool to create a generic abstraction that
allows for running matrix multiplication micro-kernels with different
interfaces.

* Extend benchmark support to all matrix multiplication micro-kernels in
 the library.

Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>

Approved-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>

Michael Kozlov authored Feb 20, 2025 and Felix Johnny Thomasmathibalan committed Feb 20, 2025

- Add new assembly ukernel optimized with FEAT_I8MM for matrix multiplication with 4x8 block size.
- Update build script.
- Add to unit test.

Signed-off-by: Michael Kozlov <michael.kozlov@arm.com>

Approved-by: Felix Johnny Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>