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Vulkan: Add DP4A MMQ and Q8_1 quantization shader (llama/12135)

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* Vulkan: Add DP4A MMQ and Q8_1 quantization shader

* Add q4_0 x q8_1 matrix matrix multiplication support

* Vulkan: Add int8 coopmat MMQ support

* Vulkan: Add q4_1, q5_0 and q5_1 quants, improve integer dot code

* Add GL_EXT_integer_dot_product check

* Remove ggml changes, fix mmq pipeline picker

* Remove ggml changes, restore Intel coopmat behaviour

* Fix glsl compile attempt when integer vec dot is not supported

* Remove redundant code, use non-saturating integer dot, enable all matmul sizes for mmq

* Remove redundant comment

* Fix integer dot check

* Fix compile issue with unsupported int dot glslc

* Update Windows build Vulkan SDK version
This commit is contained in:
0cc4m 2025-03-31 14:37:01 +02:00 committed by Georgi Gerganov
parent fc0b844eec
commit ead4d0644a
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GPG Key ID: 449E073F9DC10735
9 changed files with 1145 additions and 94 deletions
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14
ggml/src/ggml-vulkan/CMakeLists.txt
View File

@ -69,6 +69,20 @@ if (Vulkan_FOUND)
add_compile_definitions(GGML_VULKAN_COOPMAT2_GLSLC_SUPPORT)
endif()
# Compile a test shader to determine whether GL_EXT_integer_dot_product is supported.
# If it's not, there will be an error to stderr.
# If it's supported, set a define to indicate that we should compile those shaders
execute_process(COMMAND ${Vulkan_GLSLC_EXECUTABLE} -o - -fshader-stage=compute --target-env=vulkan1.3 "${CMAKE_CURRENT_SOURCE_DIR}/vulkan-shaders/test_integer_dot_support.comp"
OUTPUT_VARIABLE glslc_output
ERROR_VARIABLE glslc_error)
if (${glslc_error} MATCHES ".*extension not supported: GL_EXT_integer_dot_product.*")
message(STATUS "GL_EXT_integer_dot_product not supported by glslc")
else()
message(STATUS "GL_EXT_integer_dot_product supported by glslc")
add_compile_definitions(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
endif()
target_link_libraries(ggml-vulkan PRIVATE Vulkan::Vulkan)
target_include_directories(ggml-vulkan PRIVATE ${CMAKE_CURRENT_BINARY_DIR})

520
ggml/src/ggml-vulkan/ggml-vulkan.cpp
View File

@ -234,6 +234,8 @@ struct vk_device_struct {
bool float_controls_rte_fp16;
bool subgroup_add;
bool integer_dot_product;
bool subgroup_size_control;
uint32_t subgroup_min_size;
uint32_t subgroup_max_size;
@ -245,6 +247,12 @@ struct vk_device_struct {
uint32_t coopmat_m;
uint32_t coopmat_n;
uint32_t coopmat_k;
bool coopmat_int_support;
uint32_t coopmat_int_m;
uint32_t coopmat_int_n;
uint32_t coopmat_int_k;
bool coopmat2;
size_t idx;
@ -263,10 +271,10 @@ struct vk_device_struct {
vk_matmul_pipeline pipeline_matmul_f32_f16 {};
vk_matmul_pipeline2 pipeline_matmul_f16;
vk_matmul_pipeline2 pipeline_matmul_f16_f32;
vk_pipeline pipeline_matmul_split_k_reduce;
vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_COUNT];
vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat[GGML_TYPE_COUNT];
vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_COUNT];
vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_COUNT];
vk_matmul_pipeline pipeline_matmul_id_f32 {};
vk_matmul_pipeline2 pipeline_matmul_id_f16;
@ -274,6 +282,9 @@ struct vk_device_struct {
vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_id[GGML_TYPE_COUNT];
vk_pipeline pipeline_matmul_split_k_reduce;
vk_pipeline pipeline_quantize_q8_1;
vk_pipeline pipeline_dequant[GGML_TYPE_COUNT];
vk_pipeline pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_COUNT][mul_mat_vec_max_cols];
vk_pipeline pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_COUNT][mul_mat_vec_max_cols];
@ -640,6 +651,13 @@ struct vk_op_rwkv_wkv7_push_constants {
uint32_t H;
};
struct vk_op_upscale_push_constants {
uint32_t ne; uint32_t a_offset; uint32_t d_offset;
uint32_t nb00; uint32_t nb01; uint32_t nb02; uint32_t nb03;
uint32_t ne10; uint32_t ne11; uint32_t ne12; uint32_t ne13;
float sf0; float sf1; float sf2; float sf3;
};
// Allow pre-recording command buffers
struct vk_staging_memcpy {
vk_staging_memcpy(void * _dst, const void * _src, size_t _n) : dst(_dst), src(_src), n(_n) {}
@ -649,13 +667,6 @@ struct vk_staging_memcpy {
size_t n;
};
struct vk_op_upscale_push_constants {
uint32_t ne; uint32_t a_offset; uint32_t d_offset;
uint32_t nb00; uint32_t nb01; uint32_t nb02; uint32_t nb03;
uint32_t ne10; uint32_t ne11; uint32_t ne12; uint32_t ne13;
float sf0; float sf1; float sf2; float sf3;
};
struct vk_context_struct {
vk_submission * s;
std::vector<vk_sequence> seqs;
@ -1598,6 +1609,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
// mulmat
std::vector<uint32_t> l_warptile, m_warptile, s_warptile,
l_warptile_mmq, m_warptile_mmq, s_warptile_mmq,
l_warptile_mmq_int, m_warptile_mmq_int, s_warptile_mmq_int,
l_warptile_mmq_k, m_warptile_mmq_k, s_warptile_mmq_k,
l_warptile_mmqid, m_warptile_mmqid, s_warptile_mmqid;
std::array<uint32_t, 3> l_wg_denoms, m_wg_denoms, s_wg_denoms,
@ -1662,6 +1674,20 @@ static void ggml_vk_load_shaders(vk_device& device) {
m_warptile_mmq = { 128, 64, 64, 32, subgroup_size_8, 32, 2, tm_m, tn_m, tk_m, subgroup_size_8 };
s_warptile_mmq = { subgroup_size_32, 32, 32, 32, 32, 32, 2, tm_s, tn_s, tk_s, subgroup_size_8 };
const uint32_t tm_int_l = device->coopmat_int_support ? device->coopmat_int_m : 4;
const uint32_t tm_int_m = device->coopmat_int_support ? device->coopmat_int_m : 4;
const uint32_t tm_int_s = device->coopmat_int_support ? device->coopmat_int_m : 2;
const uint32_t tn_int_l = device->coopmat_int_support ? device->coopmat_int_n : 4;
const uint32_t tn_int_m = device->coopmat_int_support ? device->coopmat_int_n : 2;
const uint32_t tn_int_s = device->coopmat_int_support ? device->coopmat_int_n : 2;
const uint32_t tk_int_l = device->coopmat_int_support ? device->coopmat_int_k : 1;
const uint32_t tk_int_m = device->coopmat_int_support ? device->coopmat_int_k : 1;
const uint32_t tk_int_s = device->coopmat_int_support ? device->coopmat_int_k : 1;
l_warptile_mmq_int = { 128, 128, 128, 32, subgroup_size_8 * 2, 64, 2, tm_int_l, tn_int_l, tk_int_l, subgroup_size_8 };
m_warptile_mmq_int = { 128, 64, 64, 32, subgroup_size_8, 32, 2, tm_int_m, tn_int_m, tk_int_m, subgroup_size_8 };
s_warptile_mmq_int = { subgroup_size_32, 32, 32, 32, 32, 32, 2, tm_int_s, tn_int_s, tk_int_s, subgroup_size_8 };
l_mmq_wg_denoms = l_wg_denoms = {128, 128, 1 };
m_mmq_wg_denoms = m_wg_denoms = { 64, 64, 1 };
s_mmq_wg_denoms = s_wg_denoms = { 32, 32, 1 };
@ -2000,6 +2026,14 @@ static void ggml_vk_load_shaders(vk_device& device) {
if (device->mul_mat ## ID ## _s[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _len, NAMELC ## _aligned ## F16ACC ## _data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align); \
#define CREATE_MMQ(TYPE, PIPELINE_NAME, NAMELC, F16ACC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
if (device->mul_mat ## ID ## _l[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->l, #NAMELC #F16ACC "_l", NAMELC ## F16ACC ## _len, NAMELC ## F16ACC ## _data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1); \
if (device->mul_mat ## ID ## _m[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->m, #NAMELC #F16ACC "_m", NAMELC ## F16ACC ## _len, NAMELC ## F16ACC ## _data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1); \
if (device->mul_mat ## ID ## _s[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->s, #NAMELC #F16ACC "_s", NAMELC ## F16ACC ## _len, NAMELC ## F16ACC ## _data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1); \
// Create 2 variants, {f16,f32} accumulator
#define CREATE_MM2(TYPE, PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
CREATE_MM(TYPE, PIPELINE_NAME . f16acc, NAMELC, _f16acc, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
@ -2031,6 +2065,16 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(GGML_TYPE_IQ4_XS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_XS].f16acc, matmul_iq4_xs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(GGML_TYPE_IQ4_NL, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
if (device->integer_dot_product) {
CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_0].f16acc, matmul_q4_0_q8_1, _f16acc, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_1].f16acc, matmul_q4_1_q8_1, _f16acc, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0].f16acc, matmul_q5_0_q8_1, _f16acc, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1].f16acc, matmul_q5_1_q8_1, _f16acc, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0].f16acc, matmul_q8_0_q8_1, _f16acc, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
}
#endif
CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16_f32, matmul_id_f16_f32, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
@ -2056,6 +2100,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(GGML_TYPE_IQ4_XS, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS].f16acc, matmul_id_iq4_xs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(GGML_TYPE_IQ4_NL, pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
#undef CREATE_MM2
#undef CREATE_MMQ
#undef CREATE_MM
} else {
// Create 6 variants, {s,m,l}x{unaligned,aligned}
@ -2073,6 +2118,14 @@ static void ggml_vk_load_shaders(vk_device& device) {
if (device->mul_mat ## ID ## _s[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _fp32_len, NAMELC ## _aligned ## F16ACC ## _fp32_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align); \
#define CREATE_MMQ(TYPE, PIPELINE_NAME, NAMELC, F16ACC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
if (device->mul_mat ## ID ## _l[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->l, #NAMELC #F16ACC "_l", NAMELC ## F16ACC ## _fp32_len, NAMELC ## F16ACC ## _fp32_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1); \
if (device->mul_mat ## ID ## _m[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->m, #NAMELC #F16ACC "_m", NAMELC ## F16ACC ## _fp32_len, NAMELC ## F16ACC ## _fp32_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1); \
if (device->mul_mat ## ID ## _s[TYPE]) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->s, #NAMELC #F16ACC "_s", NAMELC ## F16ACC ## _fp32_len, NAMELC ## F16ACC ## _fp32_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1); \
CREATE_MM(GGML_TYPE_F32, pipeline_matmul_f32, matmul_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
CREATE_MM(GGML_TYPE_F32, pipeline_matmul_f32_f16, matmul_f32_f16, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
CREATE_MM(GGML_TYPE_F16, pipeline_matmul_f16.f32acc, matmul_f16, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
@ -2099,6 +2152,16 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(GGML_TYPE_IQ4_XS, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_XS].f32acc, matmul_iq4_xs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(GGML_TYPE_IQ4_NL, pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f32acc, matmul_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
if (device->integer_dot_product) {
CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_0].f32acc, matmul_q4_0_q8_1, , mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_1].f32acc, matmul_q4_1_q8_1, , mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0].f32acc, matmul_q5_0_q8_1, , mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1].f32acc, matmul_q5_1_q8_1, , mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0].f32acc, matmul_q8_0_q8_1, , mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
}
#endif
CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16.f32acc, matmul_id_f16, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
CREATE_MM(GGML_TYPE_F16, pipeline_matmul_id_f16_f32.f32acc, matmul_id_f16_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
@ -2132,7 +2195,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
uint32_t rm_stdq = 1;
uint32_t rm_kq = 2;
if (device->vendor_id == VK_VENDOR_ID_AMD) {
if (device->subgroup_min_size == 64 && device->subgroup_max_size == 64) { // GCN
if (device->architecture == AMD_GCN) {
rm_stdq = 2;
rm_kq = 4;
}
@ -2266,6 +2329,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ4_NL], "get_rows_iq4_nl_f32", get_rows_iq4_nl_f32_len, get_rows_iq4_nl_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_matmul_split_k_reduce, "split_k_reduce", split_k_reduce_len, split_k_reduce_data, "main", 2, 2 * sizeof(uint32_t), {256 * 4, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_quantize_q8_1, "quantize_q8_1", quantize_q8_1_len, quantize_q8_1_data, "main", 2, 1 * sizeof(uint32_t), {32 * device->subgroup_size / 8, 1, 1}, { device->subgroup_size }, 1);
for (uint32_t i = 0; i < p021_max_gqa_ratio; ++i) {
if (device->subgroup_add && device->subgroup_require_full_support) {
@ -2452,6 +2516,7 @@ static vk_device ggml_vk_get_device(size_t idx) {
bool pipeline_robustness = false;
bool coopmat2_support = false;
device->coopmat_support = false;
device->integer_dot_product = false;
for (const auto& properties : ext_props) {
if (strcmp("VK_KHR_maintenance4", properties.extensionName) == 0) {
@ -2477,6 +2542,11 @@ static vk_device ggml_vk_get_device(size_t idx) {
} else if (strcmp("VK_NV_cooperative_matrix2", properties.extensionName) == 0 &&
!getenv("GGML_VK_DISABLE_COOPMAT2")) {
coopmat2_support = true;
#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
} else if (strcmp("VK_KHR_shader_integer_dot_product", properties.extensionName) == 0 &&
!getenv("GGML_VK_DISABLE_INTEGER_DOT_PRODUCT")) {
device->integer_dot_product = true;
#endif
}
}
@ -2490,6 +2560,7 @@ static vk_device ggml_vk_get_device(size_t idx) {
vk::PhysicalDeviceVulkan11Properties vk11_props;
vk::PhysicalDeviceVulkan12Properties vk12_props;
vk::PhysicalDeviceSubgroupSizeControlPropertiesEXT subgroup_size_control_props;
vk::PhysicalDeviceShaderIntegerDotProductPropertiesKHR shader_integer_dot_product_props;
props2.pNext = &props3;
props3.pNext = &subgroup_props;
@ -2524,6 +2595,11 @@ static vk_device ggml_vk_get_device(size_t idx) {
}
#endif
if (device->integer_dot_product) {
last_struct->pNext = (VkBaseOutStructure *)&shader_integer_dot_product_props;
last_struct = (VkBaseOutStructure *)&shader_integer_dot_product_props;
}
device->physical_device.getProperties2(&props2);
device->properties = props2.properties;
device->vendor_id = device->properties.vendorID;
@ -2570,6 +2646,8 @@ static vk_device ggml_vk_get_device(size_t idx) {
device->coopmat_support = false;
}
device->integer_dot_product = device->integer_dot_product && shader_integer_dot_product_props.integerDotProduct4x8BitPackedSignedAccelerated;
std::vector<vk::QueueFamilyProperties> queue_family_props = device->physical_device.getQueueFamilyProperties();
// Try to find a non-graphics compute queue and transfer-focused queues
@ -2662,6 +2740,14 @@ static vk_device ggml_vk_get_device(size_t idx) {
device_extensions.push_back("VK_KHR_maintenance4");
}
VkPhysicalDeviceShaderIntegerDotProductFeaturesKHR shader_integer_dot_product_features {};
shader_integer_dot_product_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_INTEGER_DOT_PRODUCT_FEATURES_KHR;
if (device->integer_dot_product) {
last_struct->pNext = (VkBaseOutStructure *)&shader_integer_dot_product_features;
last_struct = (VkBaseOutStructure *)&shader_integer_dot_product_features;
device_extensions.push_back("VK_KHR_shader_integer_dot_product");
}
vkGetPhysicalDeviceFeatures2(device->physical_device, &device_features2);
device->fp16 = device->fp16 && vk12_features.shaderFloat16;
@ -2831,6 +2917,17 @@ static vk_device ggml_vk_get_device(size_t idx) {
device->coopmat_acc_f16_support = true;
}
}
} else if ((vk::ComponentTypeKHR)prop.AType == vk::ComponentTypeKHR::eSint8 &&
(vk::ComponentTypeKHR)prop.BType == vk::ComponentTypeKHR::eSint8 &&
(vk::ComponentTypeKHR)prop.CType == vk::ComponentTypeKHR::eSint32 &&
(vk::ComponentTypeKHR)prop.ResultType == vk::ComponentTypeKHR::eSint32 &&
(vk::ScopeKHR)prop.scope == vk::ScopeKHR::eSubgroup &&
device->coopmat_int_m == 0
) {
device->coopmat_int_support = true;
device->coopmat_int_m = prop.MSize;
device->coopmat_int_n = prop.NSize;
device->coopmat_int_k = prop.KSize;
}
}
@ -2935,25 +3032,11 @@ static void ggml_vk_print_gpu_info(size_t idx) {
vk::PhysicalDevice physical_device = devices[dev_num];
std::vector<vk::ExtensionProperties> ext_props = physical_device.enumerateDeviceExtensionProperties();
vk::PhysicalDeviceProperties2 props2;
vk::PhysicalDeviceMaintenance3Properties props3;
vk::PhysicalDeviceSubgroupProperties subgroup_props;
vk::PhysicalDeviceDriverProperties driver_props;
props2.pNext = &props3;
props3.pNext = &subgroup_props;
subgroup_props.pNext = &driver_props;
physical_device.getProperties2(&props2);
vk_device_architecture arch = get_device_architecture(physical_device);
uint32_t default_subgroup_size = get_subgroup_size("", arch);
const size_t subgroup_size = (default_subgroup_size != 0) ? default_subgroup_size : subgroup_props.subgroupSize;
const bool uma = props2.properties.deviceType == vk::PhysicalDeviceType::eIntegratedGpu;
bool fp16_storage = false;
bool fp16_compute = false;
bool coopmat_support = false;
bool coopmat2_support = false;
bool integer_dot_product = false;
for (auto properties : ext_props) {
if (strcmp("VK_KHR_16bit_storage", properties.extensionName) == 0) {
@ -2969,27 +3052,44 @@ static void ggml_vk_print_gpu_info(size_t idx) {
} else if (strcmp("VK_NV_cooperative_matrix2", properties.extensionName) == 0 &&
!getenv("GGML_VK_DISABLE_COOPMAT2")) {
coopmat2_support = true;
#endif
#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
} else if (strcmp("VK_KHR_shader_integer_dot_product", properties.extensionName) == 0 &&
!getenv("GGML_VK_DISABLE_INTEGER_DOT_PRODUCT")) {
integer_dot_product = true;
#endif
}
}
const vk_device_architecture device_architecture = get_device_architecture(physical_device);
if (!ggml_vk_khr_cooperative_matrix_support(props2.properties, driver_props, device_architecture)) {
coopmat_support = false;
}
const char* GGML_VK_DISABLE_F16 = getenv("GGML_VK_DISABLE_F16");
bool force_disable_f16 = GGML_VK_DISABLE_F16 != nullptr;
bool fp16 = !force_disable_f16 && fp16_storage && fp16_compute;
vk::PhysicalDeviceFeatures device_features = physical_device.getFeatures();
vk::PhysicalDeviceProperties2 props2;
vk::PhysicalDeviceMaintenance3Properties props3;
vk::PhysicalDeviceSubgroupProperties subgroup_props;
vk::PhysicalDeviceDriverProperties driver_props;
vk::PhysicalDeviceShaderIntegerDotProductPropertiesKHR shader_integer_dot_product_props;
props2.pNext = &props3;
props3.pNext = &subgroup_props;
subgroup_props.pNext = &driver_props;
// Pointer to the last chain element
VkBaseOutStructure * last_struct = (VkBaseOutStructure *)&driver_props;
if (integer_dot_product) {
last_struct->pNext = (VkBaseOutStructure *)&shader_integer_dot_product_props;
last_struct = (VkBaseOutStructure *)&shader_integer_dot_product_props;
}
physical_device.getProperties2(&props2);
VkPhysicalDeviceFeatures2 device_features2;
device_features2.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_FEATURES_2;
device_features2.pNext = nullptr;
device_features2.features = (VkPhysicalDeviceFeatures)device_features;
VkPhysicalDeviceVulkan11Features vk11_features;
vk11_features.pNext = nullptr;
@ -3002,7 +3102,7 @@ static void ggml_vk_print_gpu_info(size_t idx) {
vk11_features.pNext = &vk12_features;
// Pointer to the last chain element
VkBaseOutStructure * last_struct = (VkBaseOutStructure *)&vk12_features;
last_struct = (VkBaseOutStructure *)&vk12_features;
#if defined(GGML_VULKAN_COOPMAT_GLSLC_SUPPORT)
VkPhysicalDeviceCooperativeMatrixFeaturesKHR coopmat_features;
@ -3014,20 +3114,37 @@ static void ggml_vk_print_gpu_info(size_t idx) {
last_struct->pNext = (VkBaseOutStructure *)&coopmat_features;
last_struct = (VkBaseOutStructure *)&coopmat_features;
}
#endif
VkPhysicalDeviceShaderIntegerDotProductFeaturesKHR shader_integer_dot_product_features {};
shader_integer_dot_product_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_SHADER_INTEGER_DOT_PRODUCT_FEATURES_KHR;
if (integer_dot_product) {
last_struct->pNext = (VkBaseOutStructure *)&shader_integer_dot_product_features;
last_struct = (VkBaseOutStructure *)&shader_integer_dot_product_features;
}
vkGetPhysicalDeviceFeatures2(physical_device, &device_features2);
fp16 = fp16 && vk12_features.shaderFloat16;
coopmat_support = coopmat_support && coopmat_features.cooperativeMatrix;
#endif
uint32_t default_subgroup_size = get_subgroup_size("", device_architecture);
const size_t subgroup_size = (default_subgroup_size != 0) ? default_subgroup_size : subgroup_props.subgroupSize;
const bool uma = props2.properties.deviceType == vk::PhysicalDeviceType::eIntegratedGpu;
integer_dot_product = integer_dot_product
&& shader_integer_dot_product_props.integerDotProduct4x8BitPackedSignedAccelerated
&& shader_integer_dot_product_features.shaderIntegerDotProduct;
coopmat_support = coopmat_support
&& coopmat_features.cooperativeMatrix
&& ggml_vk_khr_cooperative_matrix_support(props2.properties, driver_props, device_architecture);
std::string matrix_cores = coopmat2_support ? "NV_coopmat2" : coopmat_support ? "KHR_coopmat" : "none";
std::string device_name = props2.properties.deviceName.data();
GGML_LOG_DEBUG("ggml_vulkan: %zu = %s (%s) | uma: %d | fp16: %d | warp size: %zu | shared memory: %d | matrix cores: %s\n",
GGML_LOG_DEBUG("ggml_vulkan: %zu = %s (%s) | uma: %d | fp16: %d | warp size: %zu | shared memory: %d | int dot: %d | matrix cores: %s\n",
idx, device_name.c_str(), driver_props.driverName.data(), uma, fp16, subgroup_size,
props2.properties.limits.maxComputeSharedMemorySize, matrix_cores.c_str());
props2.properties.limits.maxComputeSharedMemorySize, integer_dot_product, matrix_cores.c_str());
if (props2.properties.deviceType == vk::PhysicalDeviceType::eCpu) {
GGML_LOG_DEBUG("ggml_vulkan: Warning: Device type is CPU. This is probably not the device you want.\n");
@ -3293,6 +3410,17 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte
}
}
// MMQ
if (src1_type == GGML_TYPE_Q8_1) {
vk_matmul_pipeline pipelines = ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f16acc;
if (pipelines->s == nullptr && pipelines->m == nullptr && pipelines->l == nullptr) {
return nullptr;
}
return pipelines;
}
if (src1_type != GGML_TYPE_F32 && !ctx->device->coopmat2) {
return nullptr;
}
@ -3585,8 +3713,6 @@ static vk_submission ggml_vk_begin_submission(vk_device& device, vk_queue& q, bo
return s;
}
static void ggml_vk_dispatch_pipeline(ggml_backend_vk_context* ctx, vk_context& subctx, vk_pipeline& pipeline, std::initializer_list<vk::DescriptorBufferInfo> const& descriptor_buffer_infos, size_t push_constant_size, const void* push_constants, std::array<uint32_t, 3> elements) {
const uint32_t wg0 = CEIL_DIV(elements[0], pipeline->wg_denoms[0]);
const uint32_t wg1 = CEIL_DIV(elements[1], pipeline->wg_denoms[1]);
@ -4016,8 +4142,8 @@ static uint32_t ggml_vk_guess_split_k(ggml_backend_vk_context * ctx, int m, int
return split_k;
}
static vk_pipeline ggml_vk_guess_matmul_pipeline(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n, bool aligned, ggml_type src0_type) {
VK_LOG_DEBUG("ggml_vk_guess_matmul_pipeline(" << m << ", " << n << ", " << aligned << ", " << ggml_type_name(src0_type) << ")");
static vk_pipeline ggml_vk_guess_matmul_pipeline(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, uint32_t m, uint32_t n, bool aligned, ggml_type src0_type, ggml_type src1_type) {
VK_LOG_DEBUG("ggml_vk_guess_matmul_pipeline(" << m << ", " << n << ", " << aligned << ", " << ggml_type_name(src0_type) << ", " << ggml_type_name(src1_type) << ")");
if (ctx->device->coopmat2) {
// Use large shader when the N dimension is greater than the medium shader's tile size
@ -4042,9 +4168,9 @@ static vk_pipeline ggml_vk_guess_matmul_pipeline(ggml_backend_vk_context * ctx,
return aligned ? mmp->a_l : mmp->l;
}
static uint32_t ggml_vk_guess_matmul_pipeline_align(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n, ggml_type src0_type) {
VK_LOG_DEBUG("ggml_vk_guess_matmul_pipeline_align(" << m << ", " << n << ", " << ggml_type_name(src0_type) << ")");
return ggml_vk_guess_matmul_pipeline(ctx, mmp, m, n, true, src0_type)->align;
static uint32_t ggml_vk_guess_matmul_pipeline_align(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n, ggml_type src0_type, ggml_type src1_type) {
VK_LOG_DEBUG("ggml_vk_guess_matmul_pipeline_align(" << m << ", " << n << ", " << ggml_type_name(src0_type) << ", " << ggml_type_name(src1_type) << ")");
return ggml_vk_guess_matmul_pipeline(ctx, mmp, m, n, true, src0_type, src1_type)->align;
}
static void ggml_vk_matmul(
@ -4054,7 +4180,7 @@ static void ggml_vk_matmul(
uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d,
uint32_t split_k, uint32_t batch, uint32_t ne02, uint32_t ne12, uint32_t broadcast2, uint32_t broadcast3,
uint32_t padded_n) {
VK_LOG_DEBUG("ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), d: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << (split_k_buffer.buffer != nullptr ? split_k_buffer.buffer->buffer : VK_NULL_HANDLE) << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ")");
VK_LOG_DEBUG("ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), d: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << (split_k_buffer.buffer != nullptr ? split_k_buffer.buffer->buffer : VK_NULL_HANDLE) << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ", padded_n: " << padded_n << ")");
ggml_vk_sync_buffers(subctx);
if (split_k == 1) {
const vk_mat_mat_push_constants pc = { m, n, k, stride_a, stride_b, stride_d, batch_stride_a, batch_stride_b, batch_stride_d, k, ne02, ne12, broadcast2, broadcast3, padded_n };
@ -4072,7 +4198,7 @@ static void ggml_vk_matmul(
ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_matmul_split_k_reduce, { split_k_buffer, d }, pc2.size() * sizeof(uint32_t), pc2.data(), { m * n * batch, 1, 1 });
}
static vk_pipeline ggml_vk_guess_matmul_id_pipeline(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, int m, int n, bool aligned, ggml_type src0_type) {
static vk_pipeline ggml_vk_guess_matmul_id_pipeline(ggml_backend_vk_context * ctx, vk_matmul_pipeline& mmp, uint32_t m, uint32_t n, bool aligned, ggml_type src0_type) {
VK_LOG_DEBUG("ggml_vk_guess_matmul_id_pipeline(" << m << ", " << n << ", " << aligned << ", " << ggml_type_name(src0_type) << ")");
if (ctx->device->coopmat2) {
@ -4214,6 +4340,25 @@ static void ggml_vk_cpy_to_contiguous(ggml_backend_vk_context * ctx, vk_context&
ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { in, out }, sizeof(vk_op_unary_push_constants), &pc, elements);
}
static vk_pipeline ggml_vk_get_quantize_pipeline(ggml_backend_vk_context * ctx, ggml_type type) {
switch(type) {
case GGML_TYPE_Q8_1:
return ctx->device->pipeline_quantize_q8_1;
default:
std::cerr << "Missing quantize pipeline for type: " << ggml_type_name(type) << std::endl;
GGML_ABORT("fatal error");
}
}
static void ggml_vk_quantize_q8_1(ggml_backend_vk_context * ctx, vk_context& subctx, vk_subbuffer&& in, vk_subbuffer&& out, uint32_t ne) {
VK_LOG_DEBUG("ggml_vk_quantize_q8_1(" << "buffer in size=" << in.buffer->size << ", buffer out size=" << out.buffer->size << ", " << ne << ")");
vk_pipeline pipeline = ggml_vk_get_quantize_pipeline(ctx, GGML_TYPE_Q8_1);
ggml_vk_sync_buffers(subctx);
ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { in, out }, sizeof(uint32_t), &ne, { ne, 1, 1 });
}
static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
VK_LOG_DEBUG("ggml_vk_mul_mat_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
@ -4265,10 +4410,19 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
const bool y_f32_kernel = src1->type == GGML_TYPE_F32 && !y_non_contig;
vk_matmul_pipeline mmp = ggml_vk_get_mul_mat_mat_pipeline(ctx, src0->type, y_non_contig ? GGML_TYPE_F16 : src1->type, (ggml_prec)dst->op_params[0]);
bool quantize_y = ctx->device->integer_dot_product && src1->type == GGML_TYPE_F32 && ggml_is_contiguous(src1) && (ne11 * ne10) % 4 == 0;
// Check for mmq first
vk_matmul_pipeline mmp = quantize_y ? ggml_vk_get_mul_mat_mat_pipeline(ctx, src0->type, GGML_TYPE_Q8_1, (ggml_prec)dst->op_params[0]) : nullptr;
if (mmp == nullptr) {
// Fall back to f16 dequant mul mat
mmp = ggml_vk_get_mul_mat_mat_pipeline(ctx, src0->type, y_non_contig ? GGML_TYPE_F16 : src1->type, (ggml_prec)dst->op_params[0]);
quantize_y = false;
}
const bool qx_needs_dequant = mmp == nullptr || x_non_contig;
const bool qy_needs_dequant = (src1->type != GGML_TYPE_F16 && !y_f32_kernel) || y_non_contig;
const bool qy_needs_dequant = !quantize_y && ((src1->type != GGML_TYPE_F16 && !y_f32_kernel) || y_non_contig);
if (qx_needs_dequant) {
// Fall back to dequant + f16 mulmat
@ -4278,13 +4432,13 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
// Not implemented
GGML_ASSERT(y_non_contig || !qy_needs_dequant); // NOLINT
const uint32_t kpad = ggml_vk_align_size(ne10, ggml_vk_guess_matmul_pipeline_align(ctx, mmp, ne01, ne11, qx_needs_dequant ? GGML_TYPE_F16 : src0->type));
const bool aligned = ne10 == kpad && ne01 > 8 && ne11 > 8;
const uint32_t kpad = quantize_y ? 0 : ggml_vk_align_size(ne10, ggml_vk_guess_matmul_pipeline_align(ctx, mmp, ne01, ne11, qx_needs_dequant ? GGML_TYPE_F16 : src0->type, quantize_y ? GGML_TYPE_Q8_1 : (y_f32_kernel ? GGML_TYPE_F32 : src1->type)));
const bool aligned = !quantize_y && ne10 == kpad && ne01 > 8 && ne11 > 8;
vk_pipeline pipeline = ggml_vk_guess_matmul_pipeline(ctx, mmp, ne01, ne11, aligned, qx_needs_dequant ? GGML_TYPE_F16 : src0->type);
vk_pipeline pipeline = ggml_vk_guess_matmul_pipeline(ctx, mmp, ne01, ne11, aligned, qx_needs_dequant ? GGML_TYPE_F16 : src0->type, quantize_y ? GGML_TYPE_Q8_1 : (y_f32_kernel ? GGML_TYPE_F32 : src1->type));
// Reserve extra storage in the N dimension for the Y matrix, so we can avoid bounds-checking
uint32_t padded_n = qy_needs_dequant ? ROUNDUP_POW2(ne11, pipeline->wg_denoms[1]) :ne11;
uint32_t padded_n = qy_needs_dequant ? ROUNDUP_POW2(ne11, pipeline->wg_denoms[1]) : ne11;
const int x_ne = ne01 * ne00;
const int y_ne = padded_n * ne10;
const int d_ne = ne11 * ne01;
@ -4294,11 +4448,12 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
const uint64_t qx_sz = ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type);
const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type);
const uint64_t x_sz = !qx_needs_dequant ? qx_sz : sizeof(ggml_fp16_t) * x_ne;
const uint64_t y_sz = y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne;
const uint64_t y_sz = quantize_y ? (y_ne * ggml_type_size(GGML_TYPE_Q8_1) / ggml_blck_size(GGML_TYPE_Q8_1)) : (y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne);
const uint64_t d_sz = sizeof(float) * d_ne;
vk_pipeline to_fp16_vk_0 = nullptr;
vk_pipeline to_fp16_vk_1 = nullptr;
vk_pipeline to_q8_1 = nullptr;
if (x_non_contig) {
to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0, nullptr, GGML_TYPE_F16);
@ -4313,6 +4468,10 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr); // NOLINT
GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr); // NOLINT
if (quantize_y) {
to_q8_1 = ggml_vk_get_quantize_pipeline(ctx, GGML_TYPE_Q8_1);
}
if (dryrun) {
const uint64_t x_sz_upd = x_sz * ne02 * ne03;
const uint64_t y_sz_upd = y_sz * ne12 * ne13;
@ -4326,7 +4485,7 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
if (qx_needs_dequant && ctx->prealloc_size_x < x_sz_upd) {
ctx->prealloc_size_x = x_sz_upd;
}
if (qy_needs_dequant && ctx->prealloc_size_y < y_sz_upd) {
if ((qy_needs_dequant || quantize_y) && ctx->prealloc_size_y < y_sz_upd) {
ctx->prealloc_size_y = y_sz_upd;
}
if (split_k > 1 && ctx->prealloc_size_split_k < split_k_size) {
@ -4341,6 +4500,9 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
if (qy_needs_dequant) {
ggml_pipeline_request_descriptor_sets(ctx->device, to_fp16_vk_1, 1);
}
if (quantize_y) {
ggml_pipeline_request_descriptor_sets(ctx->device, to_q8_1, 1);
}
if (split_k > 1) {
ggml_pipeline_request_descriptor_sets(ctx->device, ctx->device->pipeline_matmul_split_k_reduce, 1);
}
@ -4376,6 +4538,9 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
if (qy_needs_dequant) {
d_Y = ctx->prealloc_y;
GGML_ASSERT(d_Y->size >= y_sz * ne12 * ne13);
} else if (quantize_y) {
d_Y = ctx->prealloc_y;
GGML_ASSERT(d_Y->size >= y_ne * ggml_type_size(GGML_TYPE_Q8_1) / ggml_blck_size(GGML_TYPE_Q8_1));
} else {
d_Y = d_Qy;
y_buf_offset = qy_buf_offset;
@ -4392,6 +4557,9 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
if (y_non_contig) {
ggml_vk_cpy_to_contiguous(ctx, subctx, to_fp16_vk_1, src1, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE });
}
if (quantize_y) {
ggml_vk_quantize_q8_1(ctx, subctx, { d_Qy, qy_buf_offset, VK_WHOLE_SIZE }, { d_Y, 0, VK_WHOLE_SIZE }, y_ne * ne12 * ne13);
}
uint32_t stride_batch_x = ne00*ne01;
uint32_t stride_batch_y = ne10*ne11;
@ -4400,7 +4568,7 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context& sub
stride_batch_x = src0->nb[0] / ggml_type_size(src0->type);
}
if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) {
if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant && !quantize_y) {
stride_batch_y = src1->nb[0] / ggml_type_size(src1->type);
}
@ -6929,6 +7097,10 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
}
}
if (ctx->device->need_compiles) {
ggml_vk_load_shaders(ctx->device);
}
ggml_pipeline_allocate_descriptor_sets(ctx->device);
vk_buffer d_X = ggml_vk_create_buffer_check(ctx->device, sizeof(X_TYPE) * x_ne, vk::MemoryPropertyFlagBits::eDeviceLocal);
@ -7177,6 +7349,10 @@ static void ggml_vk_test_dequant(ggml_backend_vk_context * ctx, size_t ne, ggml_
ggml_pipeline_request_descriptor_sets(ctx->device, p, 1);
if (ctx->device->need_compiles) {
ggml_vk_load_shaders(ctx->device);
}
ggml_pipeline_allocate_descriptor_sets(ctx->device);
ggml_vk_buffer_write(qx_buf, 0, qx, qx_sz);
@ -7236,66 +7412,198 @@ static void ggml_vk_test_dequant(ggml_backend_vk_context * ctx, size_t ne, ggml_
free(x_chk);
}
static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m, size_t n, size_t k, size_t batch, size_t num_it, size_t split_k, size_t shader_size, ggml_type quant) {
// This does not work without ggml q8_1 quantization support
//
// typedef uint16_t ggml_half;
// typedef uint32_t ggml_half2;
//
// #define QK8_1 32
// typedef struct {
// union {
// struct {
// ggml_half d; // delta
// ggml_half s; // d * sum(qs[i])
// } GGML_COMMON_AGGR_S;
// ggml_half2 ds;
// } GGML_COMMON_AGGR_U;
// int8_t qs[QK8_1]; // quants
// } block_q8_1;
//
// static void ggml_vk_test_quantize(ggml_backend_vk_context * ctx, size_t ne, ggml_type quant) {
// VK_LOG_DEBUG("ggml_vk_test_quantize(" << ne << ")");
// GGML_ASSERT(quant == GGML_TYPE_Q8_1);
//
// const size_t x_sz = sizeof(float) * ne;
// const size_t qx_sz = ne * ggml_type_size(quant)/ggml_blck_size(quant);
// float * x = (float *) malloc(x_sz);
// block_q8_1 * qx = (block_q8_1 *)malloc(qx_sz);
// block_q8_1 * qx_res = (block_q8_1 *)malloc(qx_sz);
// vk_buffer x_buf = ggml_vk_create_buffer_check(ctx->device, x_sz, vk::MemoryPropertyFlagBits::eDeviceLocal);
// vk_buffer qx_buf = ggml_vk_create_buffer_check(ctx->device, qx_sz, vk::MemoryPropertyFlagBits::eDeviceLocal);
//
// for (size_t i = 0; i < ne; i++) {
// x[i] = rand() / (float)RAND_MAX;
// }
//
// vk_pipeline p = ggml_vk_get_quantize_pipeline(ctx, quant);
//
// ggml_pipeline_request_descriptor_sets(ctx->device, p, 1);
//
// if (ctx->device->need_compiles) {
// ggml_vk_load_shaders(ctx->device);
// }
//
// ggml_pipeline_allocate_descriptor_sets(ctx->device);
//
// ggml_vk_buffer_write(x_buf, 0, x, x_sz);
//
// vk_context subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue);
// ggml_vk_ctx_begin(ctx->device, subctx);
// ggml_vk_quantize_q8_1(ctx, subctx, ggml_vk_subbuffer(x_buf), ggml_vk_subbuffer(qx_buf), ne);
// ggml_vk_ctx_end(subctx);
//
// auto begin = std::chrono::high_resolution_clock::now();
//
// ggml_vk_submit(subctx, ctx->fence);
// VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_quantize waitForFences");
// ctx->device->device.resetFences({ ctx->fence });
//
// auto end = std::chrono::high_resolution_clock::now();
//
// double ms_quant = std::chrono::duration_cast<std::chrono::microseconds>(end-begin).count() / 1000.0;
// ggml_vk_buffer_read(qx_buf, 0, qx, qx_sz);
//
// ggml_vk_quantize_data(x, qx_res, ne, quant);
//
// int first_err = -1;
//
// for (size_t i = 0; i < ne / 32; i++) {
// double error = std::fabs(ggml_fp16_to_fp32(qx_res[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d) - ggml_fp16_to_fp32(qx[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d));
//
// if (first_err < 0 && error > 0.1) {
// first_err = i;
// }
//
// error = std::fabs(ggml_fp16_to_fp32(qx_res[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.s) - ggml_fp16_to_fp32(qx[i].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.s));
//
// if (first_err < 0 && error > 0.1) {
// first_err = i;
// }
//
// for (size_t j = 0; j < 32; j++) {
// uint64_t error = std::abs(qx_res[i].qs[j] - qx[i].qs[j]);
//
// if (first_err < 0 && error > 1) {
// first_err = i;
// }
// }
// }
//
// std::cerr << "TEST QUANTIZE " << ggml_type_name(quant) << " time=" << ms_quant << "ms " << (first_err == -1 ? "CORRECT" : "INCORRECT") << std::endl;
//
// if (first_err != -1) {
// std::cerr << "first_error = " << first_err << std::endl;
// std::cerr << "Actual result: " << std::endl << std::endl;
// std::cout << "d=" << ggml_fp16_to_fp32(qx[first_err].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d) << " s=" << ggml_fp16_to_fp32(qx[first_err].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.s) << " ";
// for (size_t j = 0; j < 32; j++) {
// std::cout << " qs" << j << "=" << (uint32_t)qx[first_err].qs[j] << " ";
// }
// std::cerr << std::endl << std::endl << "Expected result: " << std::endl << std::endl;
// std::cout << "d=" << ggml_fp16_to_fp32(qx_res[first_err].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.d) << " s=" << ggml_fp16_to_fp32(qx_res[first_err].GGML_COMMON_AGGR_U.GGML_COMMON_AGGR_S.s) << " ";
// for (size_t j = 0; j < 32; j++) {
// std::cout << " qs" << j << "=" << (uint32_t)qx_res[first_err].qs[j] << " ";
// }
// std::cerr << std::endl;
// }
//
// ggml_vk_destroy_buffer(x_buf);
// ggml_vk_destroy_buffer(qx_buf);
//
// free(x);
// free(qx);
// free(qx_res);
// }
static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m, size_t n, size_t k, size_t batch, size_t num_it, size_t split_k, size_t shader_size, ggml_type quant, bool mmq = false) {
VK_LOG_DEBUG("ggml_vk_test_dequant_matmul(" << m << ", " << n << ", " << k << ", " << batch << ", " << num_it << ", " << split_k << ", " << ggml_type_name(quant) << ")");
const size_t x_ne = m * k * batch;
const size_t y_ne = k * n * batch;
const size_t d_ne = m * n * batch;
vk_matmul_pipeline2 * pipelines;
if (mmq) {
pipelines = ctx->device->pipeline_dequant_mul_mat_mat_q8_1;
} else {
pipelines = ctx->device->pipeline_dequant_mul_mat_mat;
}
const bool fp16acc = ctx->device->fp16;
vk_pipeline p;
std::string shname;
if (shader_size == 0) {
p = ctx->device->fp16 ? ctx->device->pipeline_dequant_mul_mat_mat[quant].f16acc->a_s : ctx->device->pipeline_dequant_mul_mat_mat[quant].f32acc->a_s;
p = fp16acc ? pipelines[quant].f16acc->a_s : pipelines[quant].f32acc->a_s;
shname = std::string(ggml_type_name(quant)) + "_ALIGNED_S";
} else if (shader_size == 1) {
p = ctx->device->fp16 ? ctx->device->pipeline_dequant_mul_mat_mat[quant].f16acc->a_m : ctx->device->pipeline_dequant_mul_mat_mat[quant].f32acc->a_m;
p = fp16acc ? pipelines[quant].f16acc->a_m : pipelines[quant].f32acc->a_m;
shname = std::string(ggml_type_name(quant)) + "_ALIGNED_M";
} else if (shader_size == 2) {
p = ctx->device->fp16 ? ctx->device->pipeline_dequant_mul_mat_mat[quant].f16acc->a_l : ctx->device->pipeline_dequant_mul_mat_mat[quant].f32acc->a_l;
p = fp16acc ? pipelines[quant].f16acc->a_l : pipelines[quant].f32acc->a_l;
shname = std::string(ggml_type_name(quant)) + "_ALIGNED_L";
} else {
GGML_ASSERT(0);
}
const size_t kpad = ggml_vk_align_size(k, p->align);
const size_t kpad = mmq ? 0 : ggml_vk_align_size(k, p->align);
if (k != kpad) {
if (mmq || k != kpad) {
if (shader_size == 0) {
p = ctx->device->fp16 ? ctx->device->pipeline_dequant_mul_mat_mat[quant].f16acc->s : ctx->device->pipeline_dequant_mul_mat_mat[quant].f32acc->s;
p = fp16acc ? pipelines[quant].f16acc->s : pipelines[quant].f32acc->s;
shname = std::string(ggml_type_name(quant)) + "_S";
} else if (shader_size == 1) {
p = ctx->device->fp16 ? ctx->device->pipeline_dequant_mul_mat_mat[quant].f16acc->m : ctx->device->pipeline_dequant_mul_mat_mat[quant].f32acc->m;
p = fp16acc ? pipelines[quant].f16acc->m : pipelines[quant].f32acc->m;
shname = std::string(ggml_type_name(quant)) + "_M";
} else if (shader_size == 2) {
p = ctx->device->fp16 ? ctx->device->pipeline_dequant_mul_mat_mat[quant].f16acc->l : ctx->device->pipeline_dequant_mul_mat_mat[quant].f32acc->l;
p = fp16acc ? pipelines[quant].f16acc->l : pipelines[quant].f32acc->l;
shname = std::string(ggml_type_name(quant)) + "_L";
} else {
GGML_ASSERT(0);
}
}
if (p == nullptr) {
std::cerr << "error: no pipeline for ggml_vk_test_dequant_matmul " << ggml_type_name(quant) << std::endl;
return;
}
const size_t x_sz = sizeof(float) * x_ne;
const size_t y_sz = sizeof(float) * y_ne;
const size_t qx_sz = x_ne * ggml_type_size(quant)/ggml_blck_size(quant);
const size_t qy_sz = mmq ? y_ne * ggml_type_size(GGML_TYPE_Q8_1)/ggml_blck_size(GGML_TYPE_Q8_1) : y_sz;
const size_t d_sz = sizeof(float) * d_ne;
float * x = (float *) malloc(x_sz);
float * y = (float *) malloc(y_sz);
void * qx = malloc(qx_sz);
vk_buffer qx_buf = ggml_vk_create_buffer_check(ctx->device, qx_sz, vk::MemoryPropertyFlagBits::eDeviceLocal);
vk_buffer y_buf = ggml_vk_create_buffer_check(ctx->device, y_sz, vk::MemoryPropertyFlagBits::eDeviceLocal);
vk_buffer qy_buf = ggml_vk_create_buffer_check(ctx->device, qy_sz, vk::MemoryPropertyFlagBits::eDeviceLocal);
vk_buffer d_buf = ggml_vk_create_buffer_check(ctx->device, d_sz, vk::MemoryPropertyFlagBits::eDeviceLocal);
float * d = (float *) malloc(d_sz);
float * d_chk = (float *) malloc(d_sz);
for (size_t i = 0; i < x_ne; i++) {
x[i] = (rand() / (float)RAND_MAX) * 2.0f - 1.0f;
// x[i] = (i % k == i / k) ? 1.0f : 0.0f;
// x[i] = i % k;
}
ggml_vk_quantize_data(x, qx, x_ne, quant);
for (size_t i = 0; i < y_ne; i++) {
// y[i] = rand() / (float)RAND_MAX;
y[i] = (i % k == i / k) ? 1.0f : 0.0f;
y[i] = (rand() / (float)RAND_MAX) * 2.0f - 1.0f;
// y[i] = (i % k == i / k) ? 1.0f : 0.0f;
// y[i] = i % k;
}
ggml_pipeline_request_descriptor_sets(ctx->device, p, num_it);
@ -7310,6 +7618,13 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m,
ctx->prealloc_split_k = ggml_vk_create_buffer_check(ctx->device, sizeof(float) * d_ne * split_k, vk::MemoryPropertyFlagBits::eDeviceLocal);
}
}
if (mmq) {
ggml_pipeline_request_descriptor_sets(ctx->device, ctx->device->pipeline_quantize_q8_1, num_it);
}
if (ctx->device->need_compiles) {
ggml_vk_load_shaders(ctx->device);
}
ggml_pipeline_allocate_descriptor_sets(ctx->device);
@ -7318,13 +7633,25 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m,
vk_context subctx = ggml_vk_create_context(ctx, ctx->device->compute_queue);
ggml_vk_ctx_begin(ctx->device, subctx);
for (size_t i = 0; i < num_it; i++) {
ggml_vk_matmul(
ctx, subctx, p, ggml_vk_subbuffer(qx_buf), ggml_vk_subbuffer(y_buf), ggml_vk_subbuffer(d_buf), ggml_vk_subbuffer(ctx->prealloc_split_k),
m, n, k,
k, k, m, k*m, k*n, m*n,
split_k, batch, batch, batch, 1, 1, n
);
if (mmq) {
for (size_t i = 0; i < num_it; i++) {
ggml_vk_quantize_q8_1(ctx, subctx, { y_buf, 0, y_sz }, { qy_buf, 0, qy_sz }, y_ne);
ggml_vk_matmul(
ctx, subctx, p, { qx_buf, 0, qx_sz }, { qy_buf, 0, qy_sz }, { d_buf, 0, d_sz }, { ctx->prealloc_split_k, 0, ctx->prealloc_size_split_k },
m, n, k,
k, k, m, k*m, k*n, m*n,
split_k, batch, batch, batch, 1, 1, n
);
}
} else {
for (size_t i = 0; i < num_it; i++) {
ggml_vk_matmul(
ctx, subctx, p, { qx_buf, 0, qx_sz }, { y_buf, 0, y_sz }, { d_buf, 0, d_sz }, { ctx->prealloc_split_k, 0, ctx->prealloc_size_split_k },
m, n, k,
k, k, m, k*m, k*n, m*n,
split_k, batch, batch, batch, 1, 1, n
);
}
}
ggml_vk_ctx_end(subctx);
@ -7382,7 +7709,11 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m,
double tflops = 2.0*m*n*k*batch*num_it / (time_ms / 1000.0) / (1000.0*1000.0*1000.0*1000.0);
std::cerr << "TEST MMQ " << shname << " m=" << m << " n=" << n << " k=" << k << " batch=" << batch << " split_k=" << split_k << " matmul " << time_ms / num_it << "ms " << tflops << " TFLOPS avg_err=" << avg_err << std::endl;
std::cerr << "TEST dequant matmul " << shname;
if (mmq) {
std::cerr << " mmq";
}
std::cerr << " m=" << m << " n=" << n << " k=" << k << " batch=" << batch << " split_k=" << split_k << " matmul " << time_ms / num_it << "ms " << tflops << " TFLOPS avg_err=" << avg_err << std::endl;
if (avg_err > 0.01 || std::isnan(avg_err)) {
std::cerr << "m = " << first_err_m << " n = " << first_err_n << " b = " << first_err_b << std::endl;
@ -7392,6 +7723,12 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m,
std::cerr << "Expected result: " << std::endl << std::endl;
ggml_vk_print_matrix_area(d_chk, GGML_TYPE_F32, m, n, first_err_m, first_err_n, first_err_b);
std::cerr << "src0: " << std::endl << std::endl;
ggml_vk_print_matrix_area(x, GGML_TYPE_F32, k, m, first_err_m, first_err_n, first_err_b);
std::cerr << std::endl;
std::cerr << "src1: " << std::endl << std::endl;
ggml_vk_print_matrix_area(y, GGML_TYPE_F32, k, n, first_err_m, first_err_n, first_err_b);
if (split_k > 1) {
float * split_k_buf = (float *) malloc(sizeof(float) * d_ne * split_k);
ggml_vk_buffer_read(ctx->prealloc_split_k, 0, split_k_buf, sizeof(float) * d_ne * split_k);
@ -7414,6 +7751,7 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m,
ggml_vk_destroy_buffer(qx_buf);
ggml_vk_destroy_buffer(y_buf);
ggml_vk_destroy_buffer(qy_buf);
ggml_vk_destroy_buffer(d_buf);
free(x);
@ -7446,7 +7784,25 @@ static void ggml_vk_preallocate_buffers(ggml_backend_vk_context * ctx) {
128, 49, 49,
4096, 49, 4096,
};
const size_t num_it = 100;
const size_t num_it = 1;
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 0, GGML_TYPE_Q4_0);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 1, GGML_TYPE_Q4_0);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 2, GGML_TYPE_Q4_0);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 0, GGML_TYPE_Q4_0, true);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 1, GGML_TYPE_Q4_0, true);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 2, GGML_TYPE_Q4_0, true);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 0, GGML_TYPE_Q8_0);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 1, GGML_TYPE_Q8_0);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 2, GGML_TYPE_Q8_0);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 0, GGML_TYPE_Q8_0, true);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 1, GGML_TYPE_Q8_0, true);
ggml_vk_test_dequant_matmul(ctx, 4096, 512, 4096, 2, num_it, 1, 2, GGML_TYPE_Q8_0, true);
abort();
for (size_t i = 0; i < vals.size(); i += 3) {
ggml_vk_test_matmul<ggml_fp16_t, float>(ctx, vals[i], vals[i + 1], vals[i + 2], 2, num_it, 1, 0);
@ -9258,7 +9614,7 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
}
if (tensor->op == GGML_OP_FLASH_ATTN_EXT) {
const float *params = (const float *)tensor->op_params;
const float * params = (const float *)tensor->op_params;
tensor_clone = ggml_flash_attn_ext(ggml_ctx, src_clone[0], src_clone[1], src_clone[2], src_clone[3], params[0], params[1], params[2]);
} else if (tensor->op == GGML_OP_MUL_MAT) {
tensor_clone = ggml_mul_mat(ggml_ctx, src_clone[0], src_clone[1]);
@ -9275,7 +9631,8 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
} else if (tensor->op == GGML_OP_UPSCALE) {
tensor_clone = ggml_upscale_ext(ggml_ctx, src_clone[0], tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3]);
} else if (tensor->op == GGML_OP_SCALE) {
tensor_clone = ggml_scale(ggml_ctx, src_clone[0], ((float *)tensor->op_params)[0]);
const float * params = (const float *)tensor->op_params;
tensor_clone = ggml_scale(ggml_ctx, src_clone[0], params[0]);
} else if (tensor->op == GGML_OP_SQR) {
tensor_clone = ggml_sqr(ggml_ctx, src_clone[0]);
} else if (tensor->op == GGML_OP_SIN) {
@ -9283,7 +9640,8 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
} else if (tensor->op == GGML_OP_COS) {
tensor_clone = ggml_cos(ggml_ctx, src_clone[0]);
} else if (tensor->op == GGML_OP_CLAMP) {
tensor_clone = ggml_clamp(ggml_ctx, src_clone[0], ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]);
const float * params = (const float *)tensor->op_params;
tensor_clone = ggml_clamp(ggml_ctx, src_clone[0], params[0], params[1]);
} else if (tensor->op == GGML_OP_PAD) {
tensor_clone = ggml_pad(ggml_ctx, src_clone[0], tensor->ne[0] - src_clone[0]->ne[0], tensor->ne[1] - src_clone[0]->ne[1], tensor->ne[2] - src_clone[0]->ne[2], tensor->ne[3] - src_clone[0]->ne[3]);
} else if (tensor->op == GGML_OP_REPEAT) {
@ -9297,7 +9655,8 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
} else if (tensor->op == GGML_OP_NORM) {
tensor_clone = ggml_norm(ggml_ctx, src_clone[0], *(float *)tensor->op_params);
} else if (tensor->op == GGML_OP_GROUP_NORM) {
tensor_clone = ggml_group_norm(ggml_ctx, src_clone[0], *(int *)tensor->op_params, ((float *)tensor->op_params)[1]);
const float * float_params = (const float *)tensor->op_params;
tensor_clone = ggml_group_norm(ggml_ctx, src_clone[0], tensor->op_params[0], float_params[1]);
} else if (tensor->op == GGML_OP_RMS_NORM) {
tensor_clone = ggml_rms_norm(ggml_ctx, src_clone[0], *(float *)tensor->op_params);
} else if (tensor->op == GGML_OP_RMS_NORM_BACK) {
@ -9310,14 +9669,15 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
tensor_clone = ggml_l2_norm(ggml_ctx, src_clone[0], eps);
} else if (tensor->op == GGML_OP_SOFT_MAX) {
if (src1 != nullptr) {
tensor_clone = ggml_soft_max_ext(ggml_ctx, src_clone[0], src_clone[1], ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]);
const float * params = (const float *)tensor->op_params;
tensor_clone = ggml_soft_max_ext(ggml_ctx, src_clone[0], src_clone[1], params[0], params[1]);
} else {
tensor_clone = ggml_soft_max(ggml_ctx, src_clone[0]);
}
} else if (tensor->op == GGML_OP_SOFT_MAX_BACK) {
tensor_clone = ggml_soft_max_ext_back(ggml_ctx, src_clone[0], src_clone[1], ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]);
} else if (tensor->op == GGML_OP_DIAG_MASK_INF) {
tensor_clone = ggml_diag_mask_inf(ggml_ctx, src_clone[0], *(int *)tensor->op_params);
tensor_clone = ggml_diag_mask_inf(ggml_ctx, src_clone[0], tensor->op_params[0]);
} else if (tensor->op == GGML_OP_ROPE || tensor->op == GGML_OP_ROPE_BACK) {
const int n_dims = ((int32_t *) tensor->op_params)[1];
const int mode = ((int32_t *) tensor->op_params)[2];

8
ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
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@ -212,7 +212,7 @@ void main() {
#else
ACC_TYPE sums[WMITER * TM * WNITER * TN];
FLOAT_TYPE cache_a[WMITER * TM];
FLOAT_TYPE cache_b[WNITER * TN];
FLOAT_TYPE cache_b[TN];
[[unroll]] for (uint i = 0; i < WMITER*TM*WNITER*TN; i++) {
sums[i] = ACC_TYPE(0.0f);
@ -744,16 +744,14 @@ void main() {
}
[[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
[[unroll]] for (uint j = 0; j < TN; j++) {
cache_b[wsic * TN + j] = buf_b[(warp_c * WN + wsic * WSUBN + tiwc * TN + j) * SHMEM_STRIDE + i];
cache_b[j] = buf_b[(warp_c * WN + wsic * WSUBN + tiwc * TN + j) * SHMEM_STRIDE + i];
}
}
[[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
[[unroll]] for (uint cc = 0; cc < TN; cc++) {
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
sums[sums_idx] = fma(ACC_TYPE(cache_a[wsir * TM + cr]), ACC_TYPE(cache_b[wsic * TN + cc]), sums[sums_idx]);
sums[sums_idx] = fma(ACC_TYPE(cache_a[wsir * TM + cr]), ACC_TYPE(cache_b[cc]), sums[sums_idx]);
}
}
}

444
ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp Normal file
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@ -0,0 +1,444 @@
#version 450
#extension GL_EXT_control_flow_attributes : enable
#extension GL_EXT_shader_16bit_storage : require
#extension GL_EXT_shader_explicit_arithmetic_types_int8 : require
#extension GL_EXT_integer_dot_product : require
#ifdef FLOAT16
#extension GL_EXT_shader_explicit_arithmetic_types_float16 : require
#endif
#ifdef COOPMAT
#extension GL_KHR_cooperative_matrix : enable
#extension GL_KHR_memory_scope_semantics : enable
#extension GL_KHR_shader_subgroup_basic : enable
#endif
#ifdef MUL_MAT_ID
#extension GL_EXT_shader_explicit_arithmetic_types_int16 : require
#endif
#include "types.comp"
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer A {A_TYPE_PACKED16 data_a[];};
#if defined(A_TYPE_PACKED32)
layout (binding = 0) readonly buffer A_PACKED32 {A_TYPE_PACKED32 data_a_packed32[];};
#endif
layout (binding = 1) readonly buffer B {block_q8_1_packed32 data_b[];};
layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};
#ifdef MUL_MAT_ID
layout (binding = 3) readonly buffer IDS {int data_ids[];};
#endif
layout (push_constant) uniform parameter
{
uint M;
uint N;
uint K;
uint stride_a;
uint stride_b;
uint stride_d;
uint batch_stride_a;
uint batch_stride_b;
uint batch_stride_d;
#ifdef MUL_MAT_ID
uint nei0;
uint nei1;
uint nbi1;
uint ne11;
#else
uint k_split;
uint ne02;
uint ne12;
uint broadcast2;
uint broadcast3;
#endif
} p;
layout (constant_id = 0) const uint BLOCK_SIZE = 64;
layout (constant_id = 1) const uint BM = 64;
layout (constant_id = 2) const uint BN = 64;
// layout (constant_id = 3) const uint BK = 32;
layout (constant_id = 4) const uint WM = 32;
layout (constant_id = 5) const uint WN = 32;
layout (constant_id = 6) const uint WMITER = 2;
layout (constant_id = 7) const uint TM = 4;
layout (constant_id = 8) const uint TN = 2;
layout (constant_id = 9) const uint TK = 1; // Only needed for coopmat
layout (constant_id = 10) const uint WARP = 32;
#define BK 32
#ifdef COOPMAT
#define SHMEM_STRIDE (BK / 4 + 4)
#else
#define SHMEM_STRIDE (BK / 4 + 1)
#endif
shared int32_t buf_a_qs[BM * SHMEM_STRIDE];
#ifndef COOPMAT
#if QUANT_AUXF == 1
shared FLOAT_TYPE buf_a_dm[BM];
#else
shared FLOAT_TYPE_VEC2 buf_a_dm[BM];
#endif
#endif
shared int32_t buf_b_qs[BN * SHMEM_STRIDE];
#ifndef COOPMAT
shared FLOAT_TYPE_VEC2 buf_b_ds[BN];
#endif
#define LOAD_VEC_A (4 * QUANT_R)
#define LOAD_VEC_B 4
#ifdef MUL_MAT_ID
shared u16vec2 row_ids[3072];
#endif // MUL_MAT_ID
#define NUM_WARPS (BLOCK_SIZE / WARP)
#ifdef COOPMAT
shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
#endif
#include "mul_mmq_funcs.comp"
void main() {
#ifdef NEEDS_INIT_IQ_SHMEM
init_iq_shmem(gl_WorkGroupSize);
#endif
#ifdef MUL_MAT_ID
const uint expert_idx = gl_GlobalInvocationID.z;
#else
const uint batch_idx = gl_GlobalInvocationID.z;
const uint i13 = batch_idx / p.ne12;
const uint i12 = batch_idx % p.ne12;
const uint i03 = i13 / p.broadcast3;
const uint i02 = i12 / p.broadcast2;
const uint batch_idx_a = i03 * p.ne02 + i02;
#endif
const uint blocks_m = (p.M + BM - 1) / BM;
const uint ir = gl_WorkGroupID.x % blocks_m;
const uint ik = gl_WorkGroupID.x / blocks_m;
const uint ic = gl_WorkGroupID.y;
const uint WNITER = (WM * WN) / (WARP * TM * TN * WMITER);
const uint WSUBM = WM / WMITER;
const uint WSUBN = WN / WNITER;
#ifdef COOPMAT
const uint warp_i = gl_SubgroupID;
const uint tiw = gl_SubgroupInvocationID;
const uint cms_per_row = WM / TM;
const uint cms_per_col = WN / TN;
const uint storestride = WARP / TM;
const uint store_r = tiw % TM;
const uint store_c = tiw / TM;
#else
const uint warp_i = gl_LocalInvocationID.x / WARP;
const uint tiw = gl_LocalInvocationID.x % WARP;
const uint tiwr = tiw % (WSUBM / TM);
const uint tiwc = tiw / (WSUBM / TM);
#endif
const uint warp_r = warp_i % (BM / WM);
const uint warp_c = warp_i / (BM / WM);
const uint loadr_a = gl_LocalInvocationID.x % (BK / LOAD_VEC_A);
const uint loadc_a = gl_LocalInvocationID.x / (BK / LOAD_VEC_A);
const uint loadr_b = gl_LocalInvocationID.x % (BK / LOAD_VEC_B);
const uint loadc_b = gl_LocalInvocationID.x / (BK / LOAD_VEC_B);
const uint loadstride_a = BLOCK_SIZE * LOAD_VEC_A / BK;
const uint loadstride_b = BLOCK_SIZE * LOAD_VEC_B / BK;
#ifdef MUL_MAT_ID
uint _ne1 = 0;
for (uint ii1 = 0; ii1 < p.nei1; ii1++) {
for (uint ii0 = 0; ii0 < p.nei0; ii0++) {
if (data_ids[ii1*p.nbi1 + ii0] == expert_idx) {
row_ids[_ne1] = u16vec2(ii0, ii1);
_ne1++;
}
}
}
barrier();
// Workgroup has no work
if (ic * BN >= _ne1) return;
#endif
#ifdef MUL_MAT_ID
const uint start_k = 0;
const uint end_k = p.K;
#else
const uint start_k = ik * p.k_split;
const uint end_k = min(p.K, (ik + 1) * p.k_split);
#endif
uint pos_a_ib = (
#ifdef MUL_MAT_ID
expert_idx * p.batch_stride_a +
#else
batch_idx_a * p.batch_stride_a +
#endif
ir * BM * p.stride_a + start_k) / BK;
#ifdef MUL_MAT_ID
uint pos_b_ib = 0;
#else
uint pos_b_ib = (batch_idx * p.batch_stride_b + ic * BN * p.stride_b + start_k) / BK;
#endif
#ifdef COOPMAT
coopmat<int8_t, gl_ScopeSubgroup, TM, TK, gl_MatrixUseA> cache_a;
coopmat<int8_t, gl_ScopeSubgroup, TK, TN, gl_MatrixUseB> cache_b;
coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_result;
coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> factors[cms_per_row * cms_per_col];
coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> sums[cms_per_row * cms_per_col];
[[unroll]] for (uint i = 0; i < cms_per_row * cms_per_col; i++) {
sums[i] = coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0.0f);
}
#else
int32_t cache_a_qs[WMITER * TM * BK / 4];
int32_t cache_b_qs[TN * BK / 4];
ACC_TYPE sums[WMITER * TM * WNITER * TN];
[[unroll]] for (uint i = 0; i < WMITER*TM*WNITER*TN; i++) {
sums[i] = ACC_TYPE(0.0f);
}
#endif
#if QUANT_AUXF == 1
FLOAT_TYPE cache_a_dm[TM];
#else
FLOAT_TYPE_VEC2 cache_a_dm[TM];
#endif
FLOAT_TYPE_VEC2 cache_b_ds[TN];
for (uint block = start_k; block < end_k; block += BK) {
[[unroll]] for (uint l = 0; loadc_a + l < BM; l += loadstride_a) {
const uint ib = pos_a_ib + (loadc_a + l) * p.stride_a / BK;
const uint iqs = loadr_a;
const uint buf_ib = loadc_a + l;
// Should ds be gated to a single thread?
if (iqs == 0) {
#if QUANT_AUXF == 1
buf_a_dm[buf_ib] = get_d(ib);
#else
buf_a_dm[buf_ib] = get_dm(ib);
#endif
}
#if QUANT_R == 1
buf_a_qs[buf_ib * SHMEM_STRIDE + iqs] = repack(ib, iqs);
#else
const i32vec2 vals = repack(ib, iqs);
buf_a_qs[buf_ib * SHMEM_STRIDE + iqs ] = vals.x;
buf_a_qs[buf_ib * SHMEM_STRIDE + iqs + 4] = vals.y;
#endif
}
[[unroll]] for (uint l = 0; loadc_b + l < BN; l += loadstride_b) {
#ifdef MUL_MAT_ID
const u16vec2 row_idx = row_ids[ic * BN + loadc_b + l];
const uint idx = pos_b_ib + row_idx.y * p.batch_stride_b / LOAD_VEC_B + (row_idx.x % p.ne11) * p.stride_b / LOAD_VEC_B + loadr_b;
const uint ib = idx / 8;
const uint iqs = idx & 0x7;
#else
const uint ib = pos_b_ib + (loadc_b + l) * p.stride_b / BK;
const uint iqs = loadr_b;
#endif
const uint buf_ib = loadc_b + l;
// Should ds be gated to a single thread?
if (iqs == 0) {
buf_b_ds[buf_ib] = FLOAT_TYPE_VEC2(data_b[ib].ds);
}
buf_b_qs[buf_ib * SHMEM_STRIDE + iqs] = data_b[ib].qs[iqs];
}
barrier();
pos_a_ib += 1;
pos_b_ib += 1;
#ifdef COOPMAT
[[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
const uint ib_a = warp_r * WM + cm_row * TM;
// Load from shared into cache
coopMatLoad(cache_a, buf_a_qs, ib_a * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutRowMajor);
// TODO: only cache values that are actually needed
[[unroll]] for (uint t_idx = 0; t_idx < TM; t_idx++) {
cache_a_dm[t_idx] = buf_a_dm[ib_a + t_idx];
}
[[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
const uint ib_b = warp_c * WN + cm_col * TN;
coopMatLoad(cache_b, buf_b_qs, ib_b * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutColumnMajor);
// TODO: only cache values that are actually needed
[[unroll]] for (uint t_idx = 0; t_idx < TN; t_idx++) {
cache_b_dm[t_idx] = buf_b_d[ib_b + t_idx];
}
cm_result = coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0);
cm_result = coopMatMulAdd(cache_a, cache_b, cm_result);
[[unroll]] for (uint col = 0; col < TN; col += storestride) {
coopmat_stage[warp_i * TM * TN + (store_c + col) * TM + store_r] = ACC_TYPE(float(cache_a_d[store_r]) * float(cache_b_d[store_c + col]));
}
coopMatLoad(factors, coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
sums[cm_col * cms_per_row + cm_row] += factors * coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(cm_result);
}
}
#else
// Load from shared into cache
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
const uint ib = warp_r * WM + wsir * WSUBM + tiwr * TM + cr;
cache_a_dm[wsir * TM + cr] = buf_a_dm[ib];
[[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
cache_a_qs[(wsir * TM + cr) * (BK / 4) + idx_k] = buf_a_qs[ib * SHMEM_STRIDE + idx_k];
}
}
}
[[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
[[unroll]] for (uint cc = 0; cc < TN; cc++) {
const uint ib = warp_c * WN + wsic * WSUBN + tiwc * TN + cc;
cache_b_ds[cc] = buf_b_ds[ib];
[[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
cache_b_qs[cc * (BK / 4) + idx_k] = buf_b_qs[ib * SHMEM_STRIDE + idx_k];
}
}
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
[[unroll]] for (uint cc = 0; cc < TN; cc++) {
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
const uint cache_a_idx = wsir * TM + cr;
const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
int32_t q_sum = 0;
[[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
q_sum += dotPacked4x8EXT(cache_a_qs[cache_a_idx * (BK / 4) + idx_k],
cache_b_qs[cc * (BK / 4) + idx_k]);
}
sums[sums_idx] += mul_q8_1(q_sum, cache_a_dm[cache_a_idx], cache_b_ds[cc]);
}
}
}
}
#endif
barrier();
}
const uint dr = ir * BM + warp_r * WM;
const uint dc = ic * BN + warp_c * WN;
#ifndef MUL_MAT_ID
const uint offsets = batch_idx * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z;
#endif
#ifdef COOPMAT
#ifdef MUL_MAT_ID
[[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
[[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
[[unroll]] for (uint col = 0; col < BN; col += storestride) {
const uint row_i = dc + cm_col * TN + col + store_c;
if (row_i >= _ne1) break;
const u16vec2 row_idx = row_ids[row_i];
data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
}
}
}
#else
const bool is_aligned = p.stride_d % 4 == 0; // Assumption: D_TYPE == float
[[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
[[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
const bool is_in_bounds = dr + (cm_row + 1) * TM <= p.M && dc + (cm_col + 1) * TN <= p.N;
if (is_aligned && is_in_bounds) {
// Full coopMat is within bounds and stride_d is aligned with 16B
coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_dtype = coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(sums[cm_col * cms_per_row + cm_row]);
coopMatStore(cm_dtype, data_d, offsets + (dc + cm_col * TN) * p.stride_d + dr + cm_row * TM, p.stride_d, gl_CooperativeMatrixLayoutColumnMajor);
} else if (is_in_bounds) {
// Full coopMat is within bounds, but stride_d is not aligned
coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
[[unroll]] for (uint col = 0; col < TN; col += storestride) {
data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
}
} else if (dr + cm_row * TM < p.M && dc + cm_col * TN < p.N) {
// Partial coopMat is within bounds
coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
[[unroll]] for (uint col = 0; col < TN; col += storestride) {
if (dr + cm_row * TM + store_r < p.M && dc + cm_col * TN + col + store_c < p.N) {
data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
}
}
}
}
}
#endif // MUL_MAT_ID
#else
[[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
[[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
const uint dr_warp = dr + wsir * WSUBM + tiwr * TM;
const uint dc_warp = dc + wsic * WSUBN + tiwc * TN;
[[unroll]] for (uint cc = 0; cc < TN; cc++) {
#ifdef MUL_MAT_ID
const uint row_i = dc_warp + cc;
if (row_i >= _ne1) break;
const u16vec2 row_idx = row_ids[row_i];
#endif // MUL_MAT_ID
[[unroll]] for (uint cr = 0; cr < TM; cr++) {
#ifdef MUL_MAT_ID
data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
#else
if (dr_warp + cr < p.M && dc_warp + cc < p.N) {
data_d[offsets + (dc_warp + cc) * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
}
#endif // MUL_MAT_ID
}
}
}
}
#endif // COOPMAT
}

99
ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.comp Normal file
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@ -0,0 +1,99 @@
#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require
#extension GL_EXT_shader_explicit_arithmetic_types_int16 : require
#extension GL_EXT_shader_explicit_arithmetic_types_int8 : require
#include "types.comp"
// Each iqs value maps to a 32-bit integer
#if defined(DATA_A_Q4_0)
i32vec2 repack(uint ib, uint iqs) {
// Use 2-byte loads since a q4_0 block (18 bytes) is not divisible by 4
const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2 ],
data_a[ib].qs[iqs * 2 + 1]);
const uint32_t vui = pack32(quants);
return i32vec2( vui & 0x0F0F0F0F,
(vui >> 4) & 0x0F0F0F0F);
}
ACC_TYPE mul_q8_1(int32_t q_sum, float da, vec2 dsb) {
return ACC_TYPE(da * (float(q_sum) * dsb.x - 8.0 * dsb.y));
}
#endif
#if defined(DATA_A_Q4_1)
i32vec2 repack(uint ib, uint iqs) {
// Use 4-byte loads since a q4_1 block (20 bytes) is divisible by 4
const uint32_t vui = data_a_packed32[ib].qs[iqs];
return i32vec2( vui & 0x0F0F0F0F,
(vui >> 4) & 0x0F0F0F0F);
}
ACC_TYPE mul_q8_1(int32_t q_sum, vec2 dma, vec2 dsb) {
return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y);
}
#endif
#if defined(DATA_A_Q5_0)
i32vec2 repack(uint ib, uint iqs) {
// Use 2-byte loads since a q5_0 block (22 bytes) is not divisible by 4
const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2 ],
data_a[ib].qs[iqs * 2 + 1]);
const uint32_t vui = pack32(quants);
const int32_t qh = int32_t((uint32_t(data_a[ib].qh[1]) << 16 | data_a[ib].qh[0]) >> (4 * iqs));
const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
| ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
const int32_t v1 = int32_t((vui >> 4) & 0x0F0F0F0F)
| (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
return i32vec2(v0, v1);
}
ACC_TYPE mul_q8_1(int32_t q_sum, float da, vec2 dsb) {
return ACC_TYPE(da * (float(q_sum) * dsb.x - 16.0 * dsb.y));
}
#endif
#if defined(DATA_A_Q5_1)
i32vec2 repack(uint ib, uint iqs) {
// Use 4-byte loads since a q5_1 block (24 bytes) is divisible by 4
const uint32_t vui = data_a_packed32[ib].qs[iqs];
const int32_t qh = int32_t(data_a_packed32[ib].qh >> (4 * iqs));
const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
| ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
const int32_t v1 = int32_t((vui >> 4) & 0x0F0F0F0F)
| (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
return i32vec2(v0, v1);
}
ACC_TYPE mul_q8_1(int32_t q_sum, vec2 dma, vec2 dsb) {
return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y);
}
#endif
#if defined(DATA_A_Q8_0)
int32_t repack(uint ib, uint iqs) {
// Use 2-byte loads since a q8_0 block (34 bytes) is not divisible by 4
return pack32(i16vec2(data_a[ib].qs[iqs * 2 ],
data_a[ib].qs[iqs * 2 + 1]));
}
ACC_TYPE mul_q8_1(int32_t q_sum, float da, vec2 dsb) {
return ACC_TYPE(float(q_sum) * da * dsb.x);
}
#endif
#if defined(DATA_A_Q4_0) || defined(DATA_A_Q5_0) || defined(DATA_A_Q8_0) || defined(DATA_A_IQ1_S) || defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_XS) || defined(DATA_A_IQ4_NL)
FLOAT_TYPE get_d(uint ib) {
return FLOAT_TYPE(data_a[ib].d);
}
#endif
#if defined(DATA_A_Q4_1) || defined(DATA_A_Q5_1)
FLOAT_TYPE_VEC2 get_dm(uint ib) {
return FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
}
#endif

77
ggml/src/ggml-vulkan/vulkan-shaders/quantize_q8_1.comp Normal file
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@ -0,0 +1,77 @@
#version 450
#extension GL_EXT_control_flow_attributes : require
#extension GL_EXT_shader_16bit_storage : require
layout (push_constant) uniform parameter
{
uint ne;
} p;
#include "types.comp"
layout(constant_id = 0) const uint GROUP_SIZE = 32;
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer A {vec4 data_a[];};
layout (binding = 1) writeonly buffer D {block_q8_1_packed32 data_b[];};
shared float shmem[GROUP_SIZE];
void quantize() {
const uint wgid = gl_WorkGroupID.x;
const uint tid = gl_LocalInvocationID.x;
// Each thread handles a vec4, so 8 threads handle a block
const uint blocks_per_group = GROUP_SIZE / 8;
const uint block_in_wg = tid / 8;
const uint ib = wgid * blocks_per_group + block_in_wg;
const uint iqs = tid % 8;
if (ib >= gl_NumWorkGroups.x * blocks_per_group) {
return;
}
const uint a_idx = ib * 8 + iqs;
vec4 vals = a_idx < p.ne ? data_a[a_idx] : vec4(0.0f);
const vec4 abs_vals = abs(vals);
// Find absolute max for each block
shmem[tid] = max(max(abs_vals.x, abs_vals.y), max(abs_vals.z, abs_vals.w));
barrier();
[[unroll]] for (uint s = 4; s > 0; s >>= 1) {
if (iqs < s) {
shmem[tid] = max(shmem[tid], shmem[tid + s]);
}
barrier();
}
const float amax = shmem[block_in_wg * 8];
const float d = amax / 127.0;
const float d_inv = d != 0.0 ? 1.0 / d : 0.0;
vals = round(vals * d_inv);
data_b[ib].qs[iqs] = pack32(i8vec4(round(vals)));
barrier();
// Calculate the sum for each block
shmem[tid] = vals.x + vals.y + vals.z + vals.w;
barrier();
[[unroll]] for (uint s = 4; s > 0; s >>= 1) {
if (iqs < s) {
shmem[tid] += shmem[tid + s];
}
barrier();
}
if (iqs == 0) {
const float sum = shmem[tid];
data_b[ib].ds = f16vec2(vec2(d, sum * d));
}
}
void main() {
quantize();
}

7
ggml/src/ggml-vulkan/vulkan-shaders/test_integer_dot_support.comp Normal file
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@ -0,0 +1,7 @@
#version 460
#extension GL_EXT_integer_dot_product : require
void main()
{
}

46
ggml/src/ggml-vulkan/vulkan-shaders/types.comp
View File

@ -1,4 +1,3 @@
#if !defined(GGML_TYPES_COMP)
#define GGML_TYPES_COMP
@ -51,6 +50,7 @@ struct block_q4_0_packed16
#if defined(DATA_A_Q4_0)
#define QUANT_K QUANT_K_Q4_0
#define QUANT_R QUANT_R_Q4_0
#define QUANT_AUXF 1
#define A_TYPE block_q4_0
#define A_TYPE_PACKED16 block_q4_0_packed16
#endif
@ -72,11 +72,19 @@ struct block_q4_1_packed16
uint16_t qs[16/2];
};
struct block_q4_1_packed32
{
f16vec2 dm;
uint32_t qs[16/4];
};
#if defined(DATA_A_Q4_1)
#define QUANT_K QUANT_K_Q4_1
#define QUANT_R QUANT_R_Q4_1
#define QUANT_AUXF 2
#define A_TYPE block_q4_1
#define A_TYPE_PACKED16 block_q4_1_packed16
#define A_TYPE_PACKED32 block_q4_1_packed32
#endif
#define QUANT_K_Q5_0 32
@ -99,6 +107,7 @@ struct block_q5_0_packed16
#if defined(DATA_A_Q5_0)
#define QUANT_K QUANT_K_Q5_0
#define QUANT_R QUANT_R_Q5_0
#define QUANT_AUXF 1
#define A_TYPE block_q5_0
#define A_TYPE_PACKED16 block_q5_0_packed16
#endif
@ -122,11 +131,20 @@ struct block_q5_1_packed16
uint16_t qs[16/2];
};
struct block_q5_1_packed32
{
f16vec2 dm;
uint qh;
uint32_t qs[16/4];
};
#if defined(DATA_A_Q5_1)
#define QUANT_K QUANT_K_Q5_1
#define QUANT_R QUANT_R_Q5_1
#define QUANT_AUXF 2
#define A_TYPE block_q5_1
#define A_TYPE_PACKED16 block_q5_1_packed16
#define A_TYPE_PACKED32 block_q5_1_packed32
#endif
#define QUANT_K_Q8_0 32
@ -142,14 +160,40 @@ struct block_q8_0_packed16
float16_t d;
int16_t qs[32/2];
};
struct block_q8_0_packed32
{
float16_t d;
int32_t qs[32/4];
};
#if defined(DATA_A_Q8_0)
#define QUANT_K QUANT_K_Q8_0
#define QUANT_R QUANT_R_Q8_0
#define QUANT_AUXF 1
#define A_TYPE block_q8_0
#define A_TYPE_PACKED16 block_q8_0_packed16
#define A_TYPE_PACKED32 block_q8_0_packed32
#endif
#define QUANT_K_Q8_1 32
#define QUANT_R_Q8_1 1
struct block_q8_1
{
f16vec2 ds;
int8_t qs[32];
};
struct block_q8_1_packed16
{
f16vec2 ds;
int16_t qs[16];
};
struct block_q8_1_packed32
{
f16vec2 ds;
int32_t qs[8];
};
// K-quants
#define QUANT_K_Q2_K 256

24
ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
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@ -295,7 +295,10 @@ void matmul_shaders(bool fp16, bool matmul_id, bool coopmat, bool coopmat2, bool
std::string aligned_b_type_f32 = coopmat2 ? "float" : fp16 ? "mat2x4" : "vec4";
std::string aligned_b_type_f16 = coopmat2 ? "float16_t" : fp16 ? "f16mat2x4" : "f16vec4";
std::map<std::string, std::string> base_dict = {{"FLOAT_TYPE", (coopmat2 || fp16) ? "float16_t" : "float"}};
std::map<std::string, std::string> base_dict = {
{"FLOAT_TYPE", (coopmat2 || fp16) ? "float16_t" : "float"},
{"FLOAT_TYPE_VEC2", (coopmat2 || fp16) ? "f16vec2" : "vec2"},
};
std::string shader_name = "matmul";
if (matmul_id) {
@ -313,9 +316,7 @@ void matmul_shaders(bool fp16, bool matmul_id, bool coopmat, bool coopmat2, bool
base_dict["COOPMAT"] = "1";
}
base_dict["ACC_TYPE"] = f16acc ? "float16_t" : "float";
std::string source_name = coopmat2 ? "mul_mm_cm2.comp" : "mul_mm.comp";
const std::string source_name = coopmat2 ? "mul_mm_cm2.comp" : "mul_mm.comp";
// Shaders with f16 B_TYPE
string_to_spv(shader_name + "_f32_f16", source_name, merge_maps(base_dict, {{"DATA_A_F32", "1"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}, }), fp16, coopmat, coopmat2, f16acc);
@ -339,14 +340,20 @@ void matmul_shaders(bool fp16, bool matmul_id, bool coopmat, bool coopmat2, bool
// don't generate f32 variants for coopmat2
if (!coopmat2) {
string_to_spv(shader_name + "_" + tname + "_f32", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a_unaligned}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"B_IS_FLOAT", "1"}}), fp16, coopmat, coopmat2, f16acc);
string_to_spv(shader_name + "_" + tname + "_f32_aligned", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f32}, {"D_TYPE", "float"}, {"B_IS_FLOAT", "1"}, {"ALIGNED", "1"}}), fp16, coopmat, coopmat2, f16acc);
string_to_spv(shader_name + "_" + tname + "_f32", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a_unaligned}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}), fp16, coopmat, coopmat2, f16acc);
string_to_spv(shader_name + "_" + tname + "_f32_aligned", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f32}, {"D_TYPE", "float"}, {"ALIGNED", "1"}}), fp16, coopmat, coopmat2, f16acc);
}
if (tname != "f16" && tname != "f32") {
string_to_spv(shader_name + "_" + tname + "_f16", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a_unaligned}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}, {"B_IS_FLOAT", "1"}}), fp16, coopmat, coopmat2, f16acc);
string_to_spv(shader_name + "_" + tname + "_f16_aligned", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f16}, {"D_TYPE", "float"}, {"B_IS_FLOAT", "1"}, {"ALIGNED", "1"}}), fp16, coopmat, coopmat2, f16acc);
string_to_spv(shader_name + "_" + tname + "_f16", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a_unaligned}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}), fp16, coopmat, coopmat2, f16acc);
string_to_spv(shader_name + "_" + tname + "_f16_aligned", source_name, merge_maps(base_dict, {{data_a_key, "1"}, {"LOAD_VEC_A", load_vec_a}, {"LOAD_VEC_B", load_vec}, {"B_TYPE", aligned_b_type_f16}, {"D_TYPE", "float"}, {"ALIGNED", "1"}}), fp16, coopmat, coopmat2, f16acc);
}
#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
if (!coopmat && !coopmat2 && !matmul_id && (tname == "q4_0" || tname == "q4_1" || tname == "q5_0" || tname == "q5_1" || tname == "q8_0")) {
string_to_spv(shader_name + "_" + tname + "_q8_1", "mul_mmq.comp", merge_maps(base_dict, {{data_a_key, "1"}, {"D_TYPE", "float"},}), fp16, coopmat, coopmat2, f16acc);
}
#endif
}
}
@ -458,6 +465,7 @@ void process_shaders() {
string_to_spv("acc_f32", "acc.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
string_to_spv("split_k_reduce", "mul_mat_split_k_reduce.comp", {});
string_to_spv("quantize_q8_1", "quantize_q8_1.comp", {});
string_to_spv("mul_f32", "mul.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});