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ggml-cpu : update KleidiAI to v1.5.0 (llama/12568)

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ggml-cpu : bug fix related to KleidiAI LHS packing

Signed-off-by: Dan Johansson <dan.johansson@arm.com>
This commit is contained in:
Dan Johansson 2025-03-25 12:10:18 +01:00 committed by Georgi Gerganov
parent c53d5c9e85
commit 15aa189329
4 changed files with 7 additions and 14 deletions
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4
ggml/src/ggml-cpu/CMakeLists.txt
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@ -357,9 +357,9 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
# Fetch KleidiAI sources:
include(FetchContent)
set(KLEIDIAI_COMMIT_TAG "v1.3.0")
set(KLEIDIAI_COMMIT_TAG "v1.5.0")
set(KLEIDIAI_DOWNLOAD_URL "https://github.com/ARM-software/kleidiai/archive/refs/tags/${KLEIDIAI_COMMIT_TAG}.tar.gz")
set(KLEIDIAI_ARCHIVE_MD5 "060bd2dc64642b091f461cc8dd7426d9")
set(KLEIDIAI_ARCHIVE_MD5 "ea22e1aefb800e9bc8c74d91633cc58e")
if (POLICY CMP0135)
cmake_policy(SET CMP0135 NEW)

9
ggml/src/ggml-cpu/kleidiai/kernels.cpp
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@ -51,11 +51,10 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
/* .run_kernel = */ kai_run_matmul_clamp_f32_qsi8d32p1x4_qsi4c32p4vlx4_1x4vl_sme2_sdot,
},
/* .lhs_info = */ {
/* .get_offset = */ kai_get_lhs_offset_lhs_quant_pack_qsi8d32p_f32,
/* .get_packed_offset = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
/* .get_offset = */ kai_get_lhs_offset_lhs_quant_pack_qsi8d32p_f32_neon,
/* .get_packed_offset = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32_neon,
/* .packed_size = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32_neon,
/* .pack_func = */ kai_run_lhs_quant_pack_qsi8d32p_f32_neon,
/* .require_aligned_m_idx = */ true,
},
/* .rhs_info = */ {
/* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32ps1s0scalef16_qsu4c32s16s0_neon,
@ -100,7 +99,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
/* .get_packed_offset = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
/* .packed_size = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
/* .pack_func = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
/* .require_aligned_m_idx = */ false,
},
/* .rhs_info = */ {
/* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,
@ -144,7 +142,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
/* .get_packed_offset = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
/* .packed_size = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
/* .pack_func = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
/* .require_aligned_m_idx = */ false,
},
/* .rhs_info = */ {
/* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,
@ -189,7 +186,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
/* .get_packed_offset = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
/* .packed_size = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
/* .pack_func = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
/* .require_aligned_m_idx = */ false,
},
/* .rhs_info = */ {
/* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,
@ -233,7 +229,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
/* .get_packed_offset = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
/* .packed_size = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
/* .pack_func = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
/* .require_aligned_m_idx = */ false,
},
/* .rhs_info = */ {
/* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,

1
ggml/src/ggml-cpu/kleidiai/kernels.h
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@ -40,7 +40,6 @@ struct lhs_packing_info {
size_t (*packed_size)(size_t m, size_t k, size_t bl, size_t mr, size_t kr, size_t sr);
void (*pack_func)(size_t m, size_t k, size_t bl, size_t mr, size_t kr, size_t sr, size_t m_idx_start, const float* lhs,
size_t lhs_stride, void* lhs_packed);
bool require_aligned_m_idx;
};
struct rhs_packing_info {

7
ggml/src/ggml-cpu/kleidiai/kleidiai.cpp
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@ -124,8 +124,7 @@ class tensor_traits : public ggml::cpu::tensor_traits {
size_t sr = kernel->get_sr();
// Calculate number of columns to be processed per thread
const bool use_multithread = lhs_info->require_aligned_m_idx && m <= mr ? false : true;
const size_t num_m_per_thread = use_multithread ? kai_roundup(m, nth) / nth : m;
const size_t num_m_per_thread = kai_roundup(m, mr * nth) / nth;
const size_t m_start = ith * num_m_per_thread;
size_t m_to_process = num_m_per_thread;
if ((m_start + m_to_process) > m) {
@ -135,11 +134,11 @@ class tensor_traits : public ggml::cpu::tensor_traits {
if(m_start < m) {
// Transform LHS
const size_t src_stride = src1->nb[1];
const float * src_ptr = reinterpret_cast<const float *>(lhs + lhs_info->get_offset(0, dst->src[1]->nb[1]));
const float * src_ptr = reinterpret_cast<const float *>(lhs + lhs_info->get_offset(m_start, dst->src[1]->nb[1]));
const size_t lhs_packed_offset = lhs_info->get_packed_offset(m_start, k, QK4_0, mr, kr, sr);
void * lhs_packed_ptr = static_cast<void *>(lhs_packed + lhs_packed_offset);
lhs_info->pack_func(m_to_process, k, QK4_0, mr, kr, sr, m_start, src_ptr, src_stride, lhs_packed_ptr);
lhs_info->pack_func(m_to_process, k, QK4_0, mr, kr, sr, 0, src_ptr, src_stride, lhs_packed_ptr);
}
ggml_barrier(params->threadpool);