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vulkan: add specific MMV kernels for IQ2 and IQ3 quants + optimizations (llama/11595)

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* vulkan: implement specialized MMV kernels for IQ2 quantizations

* vulkan: add MMV kernels for IQ3 quants

* vulkan: Increase MMV batch size and unroll IQ LUT setup

* vulkan: fix init_iq_shmem for WG sizes larger than tables

* vulkan: common batch size for all I-quants
This commit is contained in:
Rémy O 2025-02-28 09:42:52 +01:00 committed by Georgi Gerganov
parent c927830a70
commit 3bab804981
9 changed files with 509 additions and 42 deletions
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55
ggml/src/ggml-vulkan/ggml-vulkan.cpp
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@ -1987,6 +1987,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
}
} else if (device->vendor_id == VK_VENDOR_ID_INTEL)
rm_stdq = 2;
uint32_t rm_iq = 2 * rm_kq;
for (uint32_t i = 0; i < mul_mat_vec_max_cols; ++i) {
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f32_f32_"+std::to_string(i+1), mul_mat_vec_f32_f32_f32_len, mul_mat_vec_f32_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {device->subgroup_size, 2, i+1}, 1);
@ -2001,15 +2002,15 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_K][i], "mul_mat_vec_q4_k_f32_f32_"+std::to_string(i+1), mul_mat_vec_q4_k_f32_f32_len, mul_mat_vec_q4_k_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_K][i], "mul_mat_vec_q5_k_f32_f32_"+std::to_string(i+1), mul_mat_vec_q5_k_f32_f32_len, mul_mat_vec_q5_k_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q6_K][i], "mul_mat_vec_q6_k_f32_f32_"+std::to_string(i+1), mul_mat_vec_q6_k_f32_f32_len, mul_mat_vec_q6_k_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ1_S][i], "mul_mat_vec_iq1_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq1_s_f32_f32_len, mul_mat_vec_iq1_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ1_M][i], "mul_mat_vec_iq1_m_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq1_m_f32_f32_len, mul_mat_vec_iq1_m_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_XXS][i], "mul_mat_vec_iq2_xxs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xxs_f32_f32_len, mul_mat_vec_iq2_xxs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_XS][i], "mul_mat_vec_iq2_xs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xs_f32_f32_len, mul_mat_vec_iq2_xs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_S][i], "mul_mat_vec_iq2_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_s_f32_f32_len, mul_mat_vec_iq2_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ3_XXS][i], "mul_mat_vec_iq3_xxs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq3_xxs_f32_f32_len, mul_mat_vec_iq3_xxs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ3_S][i], "mul_mat_vec_iq3_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq3_s_f32_f32_len, mul_mat_vec_iq3_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ4_XS][i], "mul_mat_vec_iq4_xs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq4_xs_f32_f32_len, mul_mat_vec_iq4_xs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f32_f32_len, mul_mat_vec_iq4_nl_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ1_S][i], "mul_mat_vec_iq1_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq1_s_f32_f32_len, mul_mat_vec_iq1_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ1_M][i], "mul_mat_vec_iq1_m_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq1_m_f32_f32_len, mul_mat_vec_iq1_m_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_XXS][i], "mul_mat_vec_iq2_xxs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xxs_f32_f32_len, mul_mat_vec_iq2_xxs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_XS][i], "mul_mat_vec_iq2_xs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xs_f32_f32_len, mul_mat_vec_iq2_xs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_S][i], "mul_mat_vec_iq2_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_s_f32_f32_len, mul_mat_vec_iq2_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ3_XXS][i], "mul_mat_vec_iq3_xxs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq3_xxs_f32_f32_len, mul_mat_vec_iq3_xxs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ3_S][i], "mul_mat_vec_iq3_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq3_s_f32_f32_len, mul_mat_vec_iq3_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ4_XS][i], "mul_mat_vec_iq4_xs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq4_xs_f32_f32_len, mul_mat_vec_iq4_xs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f32_f32_len, mul_mat_vec_iq4_nl_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f16_f32_"+std::to_string(i+1), mul_mat_vec_f32_f16_f32_len, mul_mat_vec_f32_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {device->subgroup_size, 2, i+1}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_F16 ][i], "mul_mat_vec_f16_f16_f32_"+std::to_string(i+1), mul_mat_vec_f16_f16_f32_len, mul_mat_vec_f16_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {device->subgroup_size, 2, i+1}, 1);
@ -2023,15 +2024,15 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_K][i], "mul_mat_vec_q4_k_f16_f32_"+std::to_string(i+1), mul_mat_vec_q4_k_f16_f32_len, mul_mat_vec_q4_k_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_K][i], "mul_mat_vec_q5_k_f16_f32_"+std::to_string(i+1), mul_mat_vec_q5_k_f16_f32_len, mul_mat_vec_q5_k_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q6_K][i], "mul_mat_vec_q6_k_f16_f32_"+std::to_string(i+1), mul_mat_vec_q6_k_f16_f32_len, mul_mat_vec_q6_k_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ1_S][i], "mul_mat_vec_iq1_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq1_s_f16_f32_len, mul_mat_vec_iq1_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ1_M][i], "mul_mat_vec_iq1_m_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq1_m_f16_f32_len, mul_mat_vec_iq1_m_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_XXS][i], "mul_mat_vec_iq2_xxs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xxs_f16_f32_len, mul_mat_vec_iq2_xxs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_XS][i], "mul_mat_vec_iq2_xs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xs_f16_f32_len, mul_mat_vec_iq2_xs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_S][i], "mul_mat_vec_iq2_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_s_f16_f32_len, mul_mat_vec_iq2_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ3_XXS][i], "mul_mat_vec_iq3_xxs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq3_xxs_f16_f32_len, mul_mat_vec_iq3_xxs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ3_S][i], "mul_mat_vec_iq3_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq3_s_f16_f32_len, mul_mat_vec_iq3_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ4_XS][i], "mul_mat_vec_iq4_xs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq4_xs_f16_f32_len, mul_mat_vec_iq4_xs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f16_f32_len, mul_mat_vec_iq4_nl_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ1_S][i], "mul_mat_vec_iq1_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq1_s_f16_f32_len, mul_mat_vec_iq1_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ1_M][i], "mul_mat_vec_iq1_m_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq1_m_f16_f32_len, mul_mat_vec_iq1_m_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_XXS][i], "mul_mat_vec_iq2_xxs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xxs_f16_f32_len, mul_mat_vec_iq2_xxs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_XS][i], "mul_mat_vec_iq2_xs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xs_f16_f32_len, mul_mat_vec_iq2_xs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_S][i], "mul_mat_vec_iq2_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_s_f16_f32_len, mul_mat_vec_iq2_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ3_XXS][i], "mul_mat_vec_iq3_xxs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq3_xxs_f16_f32_len, mul_mat_vec_iq3_xxs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ3_S][i], "mul_mat_vec_iq3_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq3_s_f16_f32_len, mul_mat_vec_iq3_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ4_XS][i], "mul_mat_vec_iq4_xs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq4_xs_f16_f32_len, mul_mat_vec_iq4_xs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f16_f32_len, mul_mat_vec_iq4_nl_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq, i+1}, 1, true);
}
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_F32 ], "mul_mat_vec_id_f32_f32", mul_mat_vec_id_f32_f32_len, mul_mat_vec_id_f32_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {2, 1, 1}, {device->subgroup_size, 2}, 1);
@ -2046,15 +2047,15 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_K], "mul_mat_vec_id_q4_k_f32", mul_mat_vec_id_q4_k_f32_len, mul_mat_vec_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_K], "mul_mat_vec_id_q5_k_f32", mul_mat_vec_id_q5_k_f32_len, mul_mat_vec_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q6_K], "mul_mat_vec_id_q6_k_f32", mul_mat_vec_id_q6_k_f32_len, mul_mat_vec_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ1_S], "mul_mat_vec_id_iq1_s_f32", mul_mat_vec_id_iq1_s_f32_len, mul_mat_vec_id_iq1_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ1_M], "mul_mat_vec_id_iq1_m_f32", mul_mat_vec_id_iq1_m_f32_len, mul_mat_vec_id_iq1_m_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_XXS], "mul_mat_vec_id_iq2_xxs_f32", mul_mat_vec_id_iq2_xxs_f32_len, mul_mat_vec_id_iq2_xxs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_XS], "mul_mat_vec_id_iq2_xs_f32", mul_mat_vec_id_iq2_xs_f32_len, mul_mat_vec_id_iq2_xs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_S], "mul_mat_vec_id_iq2_s_f32", mul_mat_vec_id_iq2_s_f32_len, mul_mat_vec_id_iq2_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ3_XXS], "mul_mat_vec_id_iq3_xxs_f32", mul_mat_vec_id_iq3_xxs_f32_len, mul_mat_vec_id_iq3_xxs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ3_S], "mul_mat_vec_id_iq3_s_f32", mul_mat_vec_id_iq3_s_f32_len, mul_mat_vec_id_iq3_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ4_XS], "mul_mat_vec_id_iq4_xs_f32", mul_mat_vec_id_iq4_xs_f32_len, mul_mat_vec_id_iq4_xs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ4_NL], "mul_mat_vec_id_iq4_nl_f32", mul_mat_vec_id_iq4_nl_f32_len, mul_mat_vec_id_iq4_nl_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ1_S], "mul_mat_vec_id_iq1_s_f32", mul_mat_vec_id_iq1_s_f32_len, mul_mat_vec_id_iq1_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ1_M], "mul_mat_vec_id_iq1_m_f32", mul_mat_vec_id_iq1_m_f32_len, mul_mat_vec_id_iq1_m_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_XXS], "mul_mat_vec_id_iq2_xxs_f32", mul_mat_vec_id_iq2_xxs_f32_len, mul_mat_vec_id_iq2_xxs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_XS], "mul_mat_vec_id_iq2_xs_f32", mul_mat_vec_id_iq2_xs_f32_len, mul_mat_vec_id_iq2_xs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_S], "mul_mat_vec_id_iq2_s_f32", mul_mat_vec_id_iq2_s_f32_len, mul_mat_vec_id_iq2_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ3_XXS], "mul_mat_vec_id_iq3_xxs_f32", mul_mat_vec_id_iq3_xxs_f32_len, mul_mat_vec_id_iq3_xxs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ3_S], "mul_mat_vec_id_iq3_s_f32", mul_mat_vec_id_iq3_s_f32_len, mul_mat_vec_id_iq3_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ4_XS], "mul_mat_vec_id_iq4_xs_f32", mul_mat_vec_id_iq4_xs_f32_len, mul_mat_vec_id_iq4_xs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ4_NL], "mul_mat_vec_id_iq4_nl_f32", mul_mat_vec_id_iq4_nl_f32_len, mul_mat_vec_id_iq4_nl_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_iq, 1, 1}, {subgroup_size_16, rm_iq}, 1, true);
// dequant shaders
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_F32 ], "f32_to_f16", dequant_f32_len, dequant_f32_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1);

2
ggml/src/ggml-vulkan/vulkan-shaders/get_rows_quant.comp
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@ -1,5 +1,7 @@
#version 450
#extension GL_EXT_control_flow_attributes : enable
#include "types.comp"
#include "generic_binary_head.comp"
#include "dequant_funcs.comp"

90
ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq2_s.comp Normal file
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#version 450
#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require
#include "mul_mat_vec_base.comp"
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
void calc_superblock(const uint a_offset, const uint b_offset, const uint itid, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows) {
const uint y_idx = i * QUANT_K + 16 * itid;
const uint nibble_shift = 4 * (itid & 1);
const uint ib32 = itid / 2; // 0..7
uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i;
[[unroll]] for (uint n = 0; n < num_rows; ++n) {
const float d = float(data_a[ibi].d);
const uint scale = (data_a[ibi].scales[ib32] >> nibble_shift) & 0xF;
const float db = d * (0.5 + scale) * 0.25;
const uint qh = data_a[ibi].qh[ib32];
const u8vec2 qs16 = unpack8(data_a_packed16[ibi].qs[itid]);
const u8vec2 sign16 = unpack8(data_a_packed16[ibi].qs[QUANT_K / 16 + itid]);
[[unroll]] for (uint l = 0; l < 2; ++l) {
const uint8_t sign = sign16[l];
const uint qs = qs16[l] | ((qh << (8 - nibble_shift - 2 * l)) & 0x300);
const uvec2 grid = iq2s_grid[qs];
const vec4 grid0 = vec4(unpack8(grid.x));
const vec4 grid1 = vec4(unpack8(grid.y));
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
vec4 b0 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 0]);
vec4 b4 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 1]);
FLOAT_TYPE sum =
fma(FLOAT_TYPE(b0.x), FLOAT_TYPE((sign & 1) != 0 ? -grid0.x : grid0.x),
fma(FLOAT_TYPE(b0.y), FLOAT_TYPE((sign & 2) != 0 ? -grid0.y : grid0.y),
fma(FLOAT_TYPE(b0.z), FLOAT_TYPE((sign & 4) != 0 ? -grid0.z : grid0.z),
fma(FLOAT_TYPE(b0.w), FLOAT_TYPE((sign & 8) != 0 ? -grid0.w : grid0.w),
fma(FLOAT_TYPE(b4.x), FLOAT_TYPE((sign & 16) != 0 ? -grid1.x : grid1.x),
fma(FLOAT_TYPE(b4.y), FLOAT_TYPE((sign & 32) != 0 ? -grid1.y : grid1.y),
fma(FLOAT_TYPE(b4.z), FLOAT_TYPE((sign & 64) != 0 ? -grid1.z : grid1.z),
fma(FLOAT_TYPE(b4.w), FLOAT_TYPE((sign & 128) != 0 ? -grid1.w : grid1.w),
FLOAT_TYPE(0.0)))))))));
temp[j][n] = fma(db, sum, temp[j][n]);
}
}
ibi += num_blocks_per_row;
}
}
void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
uint a_offset, b_offset, d_offset;
get_offsets(a_offset, b_offset, d_offset);
const uint num_blocks_per_row = p.ncols / QUANT_K;
// 16 threads are used to process each block
const uint blocks_per_wg = gl_WorkGroupSize.x/16;
const uint tid = gl_LocalInvocationID.x;
const uint itid = tid % 16; // 0...15
const uint ix = tid / 16;
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
[[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
temp[j][i] = FLOAT_TYPE(0);
}
}
[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += blocks_per_wg)
calc_superblock(a_offset, b_offset, itid, i, num_blocks_per_row, first_row, num_rows);
reduce_result(temp, d_offset, first_row, num_rows, tid);
}
void main() {
const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
init_iq_shmem(gl_WorkGroupSize);
// do NUM_ROWS at a time, unless there aren't enough remaining rows
if (first_row + NUM_ROWS <= p.stride_d) {
compute_outputs(first_row, NUM_ROWS);
} else {
if (first_row >= p.stride_d) {
return;
}
compute_outputs(first_row, p.stride_d - first_row);
}
}

87
ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq2_xs.comp Normal file
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#version 450
#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require
#include "mul_mat_vec_base.comp"
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
void calc_superblock(const uint a_offset, const uint b_offset, const uint itid, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows) {
const uint y_idx = i * QUANT_K + 16 * itid;
const uint nibble_shift = 4 * (itid & 1);
const uint ib32 = itid / 2; // 0..7
uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i;
[[unroll]] for (uint n = 0; n < num_rows; ++n) {
const float d = float(data_a[ibi].d);
const uint scale = (data_a[ibi].scales[ib32] >> nibble_shift) & 0xF;
const float db = d * (0.5 + scale) * 0.25;
[[unroll]] for (uint l = 0; l < 2; ++l) {
const uint qs = data_a[ibi].qs[2 * itid + l];
const uint sign = qs >> 9;
const uint sign7 = bitCount(sign);
const vec4 grid0 = vec4(unpack8(iq2xs_grid[qs & 511].x));
const vec4 grid1 = vec4(unpack8(iq2xs_grid[qs & 511].y));
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
vec4 b0 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 0]);
vec4 b4 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 1]);
FLOAT_TYPE sum =
fma(FLOAT_TYPE(b0.x), FLOAT_TYPE((sign & 1) != 0 ? -grid0.x : grid0.x),
fma(FLOAT_TYPE(b0.y), FLOAT_TYPE((sign & 2) != 0 ? -grid0.y : grid0.y),
fma(FLOAT_TYPE(b0.z), FLOAT_TYPE((sign & 4) != 0 ? -grid0.z : grid0.z),
fma(FLOAT_TYPE(b0.w), FLOAT_TYPE((sign & 8) != 0 ? -grid0.w : grid0.w),
fma(FLOAT_TYPE(b4.x), FLOAT_TYPE((sign & 16) != 0 ? -grid1.x : grid1.x),
fma(FLOAT_TYPE(b4.y), FLOAT_TYPE((sign & 32) != 0 ? -grid1.y : grid1.y),
fma(FLOAT_TYPE(b4.z), FLOAT_TYPE((sign & 64) != 0 ? -grid1.z : grid1.z),
fma(FLOAT_TYPE(b4.w), FLOAT_TYPE((sign7 & 1) != 0 ? -grid1.w : grid1.w),
FLOAT_TYPE(0.0)))))))));
temp[j][n] = fma(db, sum, temp[j][n]);
}
}
ibi += num_blocks_per_row;
}
}
void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
uint a_offset, b_offset, d_offset;
get_offsets(a_offset, b_offset, d_offset);
const uint num_blocks_per_row = p.ncols / QUANT_K;
// 16 threads are used to process each block
const uint blocks_per_wg = gl_WorkGroupSize.x/16;
const uint tid = gl_LocalInvocationID.x;
const uint itid = tid % 16; // 0...15
const uint ix = tid / 16;
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
[[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
temp[j][i] = FLOAT_TYPE(0);
}
}
[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += blocks_per_wg)
calc_superblock(a_offset, b_offset, itid, i, num_blocks_per_row, first_row, num_rows);
reduce_result(temp, d_offset, first_row, num_rows, tid);
}
void main() {
const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
init_iq_shmem(gl_WorkGroupSize);
// do NUM_ROWS at a time, unless there aren't enough remaining rows
if (first_row + NUM_ROWS <= p.stride_d) {
compute_outputs(first_row, NUM_ROWS);
} else {
if (first_row >= p.stride_d) {
return;
}
compute_outputs(first_row, p.stride_d - first_row);
}
}

87
ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq2_xxs.comp Normal file
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#version 450
#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require
#include "mul_mat_vec_base.comp"
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
void calc_superblock(const uint a_offset, const uint b_offset, const uint itid, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows) {
const uint y_idx = i * QUANT_K + 16 * itid;
const uint ib32 = itid / 2; // 0..7
uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i;
[[unroll]] for (uint n = 0; n < num_rows; ++n) {
const float d = float(data_a[ibi].d);
const uint signscale = pack32(u16vec2(
data_a_packed16[ibi].qs[4 * ib32 + 2],
data_a_packed16[ibi].qs[4 * ib32 + 3]));
const float db = d * 0.25 * (0.5 + (signscale >> 28));
[[unroll]] for (uint l = 0; l < 2; ++l) {
const uint qs = data_a[ibi].qs[8 * ib32 + 2 * (itid & 1) + l];
const uint sign = bitfieldExtract(signscale, 7 * int(2 * (itid & 1) + l), 7);
const uint sign7 = bitCount(sign);
const vec4 grid0 = vec4(unpack8(iq2xxs_grid[qs].x));
const vec4 grid1 = vec4(unpack8(iq2xxs_grid[qs].y));
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
const vec4 b0 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 0]);
const vec4 b4 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 1]);
FLOAT_TYPE sum =
fma(FLOAT_TYPE(b0.x), FLOAT_TYPE((sign & 1) != 0 ? -grid0.x : grid0.x),
fma(FLOAT_TYPE(b0.y), FLOAT_TYPE((sign & 2) != 0 ? -grid0.y : grid0.y),
fma(FLOAT_TYPE(b0.z), FLOAT_TYPE((sign & 4) != 0 ? -grid0.z : grid0.z),
fma(FLOAT_TYPE(b0.w), FLOAT_TYPE((sign & 8) != 0 ? -grid0.w : grid0.w),
fma(FLOAT_TYPE(b4.x), FLOAT_TYPE((sign & 16) != 0 ? -grid1.x : grid1.x),
fma(FLOAT_TYPE(b4.y), FLOAT_TYPE((sign & 32) != 0 ? -grid1.y : grid1.y),
fma(FLOAT_TYPE(b4.z), FLOAT_TYPE((sign & 64) != 0 ? -grid1.z : grid1.z),
fma(FLOAT_TYPE(b4.w), FLOAT_TYPE((sign7 & 1) != 0 ? -grid1.w : grid1.w),
FLOAT_TYPE(0.0)))))))));
temp[j][n] = fma(db, sum, temp[j][n]);
}
}
ibi += num_blocks_per_row;
}
}
void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
uint a_offset, b_offset, d_offset;
get_offsets(a_offset, b_offset, d_offset);
const uint num_blocks_per_row = p.ncols / QUANT_K;
// 16 threads are used to process each block
const uint blocks_per_wg = gl_WorkGroupSize.x/16;
const uint tid = gl_LocalInvocationID.x;
const uint itid = tid % 16; // 0...15
const uint ix = tid / 16;
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
[[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
temp[j][i] = FLOAT_TYPE(0);
}
}
[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += blocks_per_wg)
calc_superblock(a_offset, b_offset, itid, i, num_blocks_per_row, first_row, num_rows);
reduce_result(temp, d_offset, first_row, num_rows, tid);
}
void main() {
const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
init_iq_shmem(gl_WorkGroupSize);
// do NUM_ROWS at a time, unless there aren't enough remaining rows
if (first_row + NUM_ROWS <= p.stride_d) {
compute_outputs(first_row, NUM_ROWS);
} else {
if (first_row >= p.stride_d) {
return;
}
compute_outputs(first_row, p.stride_d - first_row);
}
}

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ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq3_s.comp Normal file
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#version 450
#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require
#include "mul_mat_vec_base.comp"
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
void calc_superblock(const uint a_offset, const uint b_offset, const uint ib32, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows) {
const uint y_idx = i * QUANT_K + 32 * ib32;
uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i;
[[unroll]] for (uint n = 0; n < num_rows; ++n) {
const float d = float(data_a[ibi].d);
const uint scale = (data_a[ibi].scales[ib32/2] >> (4 * (ib32 & 1))) & 0xF;
const float dscale = d * (1 + 2 * scale);
const uint qh = data_a[ibi].qh[ib32];
FLOAT_TYPE sum[NUM_COLS];
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
sum[j] = 0.0;
}
[[unroll]] for (uint l = 0; l < 4; ++l) {
const u8vec2 qs = unpack8(data_a_packed16[ibi].qs[4 * ib32 + l]);
const uint sign = data_a[ibi].signs[4 * ib32 + l];
const vec4 grid0 = vec4(unpack8(iq3s_grid[qs.x | ((qh << (8 - 2*l)) & 0x100)]));
const vec4 grid1 = vec4(unpack8(iq3s_grid[qs.y | ((qh << (7 - 2*l)) & 0x100)]));
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
const vec4 b0 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 0]);
const vec4 b4 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 1]);
sum[j] =
fma(FLOAT_TYPE(b0.x), FLOAT_TYPE((sign & 1) != 0 ? -grid0.x : grid0.x),
fma(FLOAT_TYPE(b0.y), FLOAT_TYPE((sign & 2) != 0 ? -grid0.y : grid0.y),
fma(FLOAT_TYPE(b0.z), FLOAT_TYPE((sign & 4) != 0 ? -grid0.z : grid0.z),
fma(FLOAT_TYPE(b0.w), FLOAT_TYPE((sign & 8) != 0 ? -grid0.w : grid0.w),
fma(FLOAT_TYPE(b4.x), FLOAT_TYPE((sign & 16) != 0 ? -grid1.x : grid1.x),
fma(FLOAT_TYPE(b4.y), FLOAT_TYPE((sign & 32) != 0 ? -grid1.y : grid1.y),
fma(FLOAT_TYPE(b4.z), FLOAT_TYPE((sign & 64) != 0 ? -grid1.z : grid1.z),
fma(FLOAT_TYPE(b4.w), FLOAT_TYPE((sign & 128) != 0 ? -grid1.w : grid1.w),
sum[j]))))))));
}
}
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
temp[j][n] = fma(dscale, sum[j], temp[j][n]);
}
ibi += num_blocks_per_row;
}
}
void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
uint a_offset, b_offset, d_offset;
get_offsets(a_offset, b_offset, d_offset);
const uint num_blocks_per_row = p.ncols / QUANT_K;
// 8 threads are used to process each block
const uint blocks_per_wg = gl_WorkGroupSize.x/8;
const uint tid = gl_LocalInvocationID.x;
const uint itid = tid % 8; // 0...7
const uint ix = tid / 8;
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
[[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
temp[j][i] = FLOAT_TYPE(0);
}
}
[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += blocks_per_wg)
calc_superblock(a_offset, b_offset, itid, i, num_blocks_per_row, first_row, num_rows);
reduce_result(temp, d_offset, first_row, num_rows, tid);
}
void main() {
const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
init_iq_shmem(gl_WorkGroupSize);
// do NUM_ROWS at a time, unless there aren't enough remaining rows
if (first_row + NUM_ROWS <= p.stride_d) {
compute_outputs(first_row, NUM_ROWS);
} else {
if (first_row >= p.stride_d) {
return;
}
compute_outputs(first_row, p.stride_d - first_row);
}
}

88
ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq3_xxs.comp Normal file
View File

@ -0,0 +1,88 @@
#version 450
#extension GL_EXT_shader_explicit_arithmetic_types_int32 : require
#include "mul_mat_vec_base.comp"
layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
void calc_superblock(const uint a_offset, const uint b_offset, const uint itid, const uint i, const uint num_blocks_per_row, const uint first_row, const uint num_rows) {
const uint y_idx = i * QUANT_K + 16 * itid;
const uint ib32 = itid / 2; // 0..7
uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i;
[[unroll]] for (uint n = 0; n < num_rows; ++n) {
const float d = float(data_a[ibi].d);
const uint signscale = pack32(u16vec2(
data_a_packed16[ibi].qs[QUANT_K / 8 + 2 * ib32],
data_a_packed16[ibi].qs[QUANT_K / 8 + 2 * ib32 + 1]));
const float db = d * 0.5 * (0.5 + (signscale >> 28));
[[unroll]] for (uint l = 0; l < 2; ++l) {
const uint qs0 = data_a[ibi].qs[8 * ib32 + 4 * (itid & 1) + 2 * l];
const uint qs1 = data_a[ibi].qs[8 * ib32 + 4 * (itid & 1) + 2 * l + 1];
const uint sign = bitfieldExtract(signscale, 7 * int(2 * (itid & 1) + l), 7);
const uint sign7 = bitCount(sign);
const vec4 grid0 = vec4(unpack8(iq3xxs_grid[qs0]));
const vec4 grid1 = vec4(unpack8(iq3xxs_grid[qs1]));
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
const vec4 b0 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 0]);
const vec4 b4 = vec4(data_b_v4[(j*p.batch_stride_b + b_offset + y_idx) / 4 + 2*l + 1]);
FLOAT_TYPE sum =
fma(FLOAT_TYPE(b0.x), FLOAT_TYPE((sign & 1) != 0 ? -grid0.x : grid0.x),
fma(FLOAT_TYPE(b0.y), FLOAT_TYPE((sign & 2) != 0 ? -grid0.y : grid0.y),
fma(FLOAT_TYPE(b0.z), FLOAT_TYPE((sign & 4) != 0 ? -grid0.z : grid0.z),
fma(FLOAT_TYPE(b0.w), FLOAT_TYPE((sign & 8) != 0 ? -grid0.w : grid0.w),
fma(FLOAT_TYPE(b4.x), FLOAT_TYPE((sign & 16) != 0 ? -grid1.x : grid1.x),
fma(FLOAT_TYPE(b4.y), FLOAT_TYPE((sign & 32) != 0 ? -grid1.y : grid1.y),
fma(FLOAT_TYPE(b4.z), FLOAT_TYPE((sign & 64) != 0 ? -grid1.z : grid1.z),
fma(FLOAT_TYPE(b4.w), FLOAT_TYPE((sign7 & 1) != 0 ? -grid1.w : grid1.w),
FLOAT_TYPE(0.0)))))))));
temp[j][n] = fma(db, sum, temp[j][n]);
}
}
ibi += num_blocks_per_row;
}
}
void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
uint a_offset, b_offset, d_offset;
get_offsets(a_offset, b_offset, d_offset);
const uint num_blocks_per_row = p.ncols / QUANT_K;
// 16 threads are used to process each block
const uint blocks_per_wg = gl_WorkGroupSize.x/16;
const uint tid = gl_LocalInvocationID.x;
const uint itid = tid % 16; // 0...15
const uint ix = tid / 16;
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
[[unroll]] for (uint i = 0; i < NUM_ROWS; ++i) {
temp[j][i] = FLOAT_TYPE(0);
}
}
[[unroll]] for (uint i = ix; i < num_blocks_per_row; i += blocks_per_wg)
calc_superblock(a_offset, b_offset, itid, i, num_blocks_per_row, first_row, num_rows);
reduce_result(temp, d_offset, first_row, num_rows, tid);
}
void main() {
const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
init_iq_shmem(gl_WorkGroupSize);
// do NUM_ROWS at a time, unless there aren't enough remaining rows
if (first_row + NUM_ROWS <= p.stride_d) {
compute_outputs(first_row, NUM_ROWS);
} else {
if (first_row >= p.stride_d) {
return;
}
compute_outputs(first_row, p.stride_d - first_row);
}
}

50
ggml/src/ggml-vulkan/vulkan-shaders/types.comp
View File

@ -466,10 +466,13 @@ shared uint16_t iq1s_grid[2048];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq1s_grid_const.length(); i += wgsize.x) {
u16vec2 g = unpack16(iq1s_grid_const[i]);
iq1s_grid[2*i+0] = g.x;
iq1s_grid[2*i+1] = g.y;
[[unroll]] for (uint i = 0; i < iq1s_grid_const.length(); i += wgsize.x) {
uint idx = i + gl_LocalInvocationIndex.x;
if (iq1s_grid_const.length() % wgsize.x == 0 || idx < iq1s_grid_const.length()) {
u16vec2 g = unpack16(iq1s_grid_const[idx]);
iq1s_grid[2*idx+0] = g.x;
iq1s_grid[2*idx+1] = g.y;
}
}
barrier();
}
@ -565,8 +568,10 @@ shared uvec2 iq2xxs_grid[256];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq2xxs_grid.length(); i += wgsize.x) {
iq2xxs_grid[i] = iq2xxs_grid_const[i];
[[unroll]] for (uint i = 0; i < iq2xxs_grid.length(); i += wgsize.x) {
if (iq2xxs_grid_const.length() % wgsize.x == 0 || i + gl_LocalInvocationIndex.x < iq2xxs_grid_const.length()) {
iq2xxs_grid[i + gl_LocalInvocationIndex.x] = iq2xxs_grid_const[i + gl_LocalInvocationIndex.x];
}
}
barrier();
}
@ -733,8 +738,10 @@ shared uvec2 iq2xs_grid[512];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq2xs_grid.length(); i += wgsize.x) {
iq2xs_grid[i] = iq2xs_grid_const[i];
[[unroll]] for (uint i = 0; i < iq2xs_grid.length(); i += wgsize.x) {
if (iq2xs_grid.length() % wgsize.x == 0 || i + gl_LocalInvocationIndex.x < iq2xs_grid_const.length()) {
iq2xs_grid[i + gl_LocalInvocationIndex.x] = iq2xs_grid_const[i + gl_LocalInvocationIndex.x];
}
}
barrier();
}
@ -756,6 +763,14 @@ struct block_iq2_s
uint8_t scales[QUANT_K_IQ2_S/32];
};
struct block_iq2_s_packed16
{
float16_t d;
uint16_t qs[QUANT_K_IQ2_S/8];
uint16_t qh[QUANT_K_IQ2_S/64];
uint16_t scales[QUANT_K_IQ2_S/64];
};
#if defined(DATA_A_IQ2_S)
const uvec2 iq2s_grid_const[1024] = {
@ -1023,8 +1038,10 @@ shared uvec2 iq2s_grid[1024];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq2s_grid.length(); i += wgsize.x) {
iq2s_grid[i] = iq2s_grid_const[i];
[[unroll]] for (uint i = 0; i < iq2s_grid.length(); i += wgsize.x) {
if (iq2s_grid.length() % wgsize.x == 0 || i + gl_LocalInvocationIndex.x < iq2s_grid_const.length()) {
iq2s_grid[i + gl_LocalInvocationIndex.x] = iq2s_grid_const[i + gl_LocalInvocationIndex.x];
}
}
barrier();
}
@ -1032,6 +1049,7 @@ void init_iq_shmem(uvec3 wgsize)
#define QUANT_K QUANT_K_IQ2_S
#define QUANT_R QUANT_R_IQ2_S
#define A_TYPE block_iq2_s
#define A_TYPE_PACKED16 block_iq2_s_packed16
#endif
#define QUANT_K_IQ3_XXS 256
@ -1092,8 +1110,10 @@ shared uint32_t iq3xxs_grid[256];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq3xxs_grid.length(); i += wgsize.x) {
iq3xxs_grid[i] = iq3xxs_grid_const[i];
[[unroll]] for (uint i = 0; i < iq3xxs_grid.length(); i += wgsize.x) {
if (iq3xxs_grid.length() % wgsize.x == 0 || i + gl_LocalInvocationIndex.x < iq3xxs_grid.length()) {
iq3xxs_grid[i + gl_LocalInvocationIndex.x] = iq3xxs_grid_const[i + gl_LocalInvocationIndex.x];
}
}
barrier();
}
@ -1200,8 +1220,10 @@ shared uint32_t iq3s_grid[512];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq3s_grid.length(); i += wgsize.x) {
iq3s_grid[i] = iq3s_grid_const[i];
[[unroll]] for (uint i = 0; i < iq3s_grid.length(); i += wgsize.x) {
if (iq3s_grid.length() % wgsize.x == 0 || i + gl_LocalInvocationIndex.x < iq3s_grid.length()) {
iq3s_grid[i + gl_LocalInvocationIndex.x] = iq3s_grid_const[i + gl_LocalInvocationIndex.x];
}
}
barrier();
}

2
ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
View File

@ -402,7 +402,7 @@ void process_shaders() {
for (const auto& tname : type_names) {
// mul mat vec
std::string data_a_key = "DATA_A_" + to_uppercase(tname);
std::string shader = (string_ends_with(tname, "_k") || string_starts_with(tname, "iq1_")) ? "mul_mat_vec_" + tname + ".comp" : "mul_mat_vec.comp";
std::string shader = (string_ends_with(tname, "_k") || string_starts_with(tname, "iq1_") || string_starts_with(tname, "iq2_") || string_starts_with(tname, "iq3_")) ? "mul_mat_vec_" + tname + ".comp" : "mul_mat_vec.comp";
string_to_spv("mul_mat_vec_" + tname + "_f32_f32", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float"}, {"B_TYPE_VEC2", "vec2"}, {"B_TYPE_VEC4", "vec4"}, {"D_TYPE", "float"}}));
string_to_spv("mul_mat_vec_" + tname + "_f16_f32", shader, merge_maps(base_dict, {{data_a_key, "1"}, {"B_TYPE", "float16_t"}, {"B_TYPE_VEC2", "f16vec2"}, {"B_TYPE_VEC4", "f16vec4"}, {"D_TYPE", "float"}}));