vulkan: implement GGML_OP_SUB

ggml/src/ggml-vulkan/ggml-vulkan.cpp

@@ -221,6 +221,7 @@ struct vk_device_struct {
     vk_pipeline pipeline_acc_f32;
     vk_pipeline pipeline_add_f32, pipeline_add_f32_norepeat;
     vk_pipeline pipeline_add_f16_f32_f16, pipeline_add_f16_f32_f16_norepeat;
+    vk_pipeline pipeline_sub_f32, pipeline_sub_f32_norepeat;
     vk_pipeline pipeline_mul_f32, pipeline_mul_f32_norepeat;
     vk_pipeline pipeline_div_f32, pipeline_div_f32_norepeat;
     vk_pipeline pipeline_concat_f32, pipeline_concat_f16, pipeline_concat_i32;
@@ -2100,6 +2101,8 @@ static void ggml_vk_load_shaders(vk_device& device) {
 
     ggml_vk_create_pipeline(device, device->pipeline_acc_f32, "acc_f32", acc_f32_len, acc_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {}, 1);
 
+    ggml_vk_create_pipeline(device, device->pipeline_sub_f32, "sub_f32", sub_f32_len, sub_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {0}, 1);
+    ggml_vk_create_pipeline(device, device->pipeline_sub_f32_norepeat, "sub_f32_norepeat", sub_f32_len, sub_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {1}, 1);
     ggml_vk_create_pipeline(device, device->pipeline_mul_f32, "mul_f32", mul_f32_len, mul_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {0}, 1);
     ggml_vk_create_pipeline(device, device->pipeline_mul_f32_norepeat, "mul_f32_norepeat", mul_f32_len, mul_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {1}, 1);
     ggml_vk_create_pipeline(device, device->pipeline_div_f32, "div_f32", div_f32_len, div_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {512, 1, 1}, {0}, 1);
@@ -5126,6 +5129,11 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
             return ggml_are_same_shape(src0, src1) ? ctx->device->pipeline_add_f16_f32_f16_norepeat : ctx->device->pipeline_add_f16_f32_f16;
         }
         return nullptr;
+    case GGML_OP_SUB:
+        if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
+            return ggml_are_same_shape(src0, src1) ? ctx->device->pipeline_sub_f32_norepeat : ctx->device->pipeline_sub_f32;
+        }
+        return nullptr;
     case GGML_OP_MUL:
         if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
             return ggml_are_same_shape(src0, src1) ? ctx->device->pipeline_mul_f32_norepeat : ctx->device->pipeline_mul_f32;
@@ -5330,6 +5338,7 @@ static bool ggml_vk_op_supports_incontiguous(ggml_op op) {
     case GGML_OP_CPY:
     case GGML_OP_GET_ROWS:
     case GGML_OP_ADD:
+    case GGML_OP_SUB:
     case GGML_OP_MUL:
     case GGML_OP_DIV:
     case GGML_OP_CONCAT:
@@ -5614,6 +5623,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
             elements = { N * OC * OH * OW, 1, 1};
         } break;
     case GGML_OP_ADD:
+    case GGML_OP_SUB:
     case GGML_OP_DIV:
     case GGML_OP_MUL:
     case GGML_OP_SCALE:
@@ -5745,6 +5755,21 @@ static void ggml_vk_add(ggml_backend_vk_context * ctx, vk_context& subctx, const
     }, dryrun);
 }
 
+static void ggml_vk_sub(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+    const uint32_t src0_type_size = ggml_type_size(src0->type);
+    const uint32_t src1_type_size = ggml_type_size(src1->type);
+    const uint32_t dst_type_size = ggml_type_size(dst->type);
+
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SUB, {
+        (uint32_t)ggml_nelements(src0),
+        (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+        (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+        (uint32_t) dst->ne[0], (uint32_t) dst->ne[1], (uint32_t) dst->ne[2],(uint32_t) dst->ne[3], (uint32_t) dst->nb[0] /  dst_type_size, (uint32_t) dst->nb[1] /  dst_type_size, (uint32_t) dst->nb[2] /  dst_type_size, (uint32_t) dst->nb[3] /  dst_type_size,
+        0,
+        0.0f, 0.0f, 0,
+    }, dryrun);
+}
+
 static void ggml_vk_mul(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
     const uint32_t src0_type_size = ggml_type_size(src0->type);
     const uint32_t src1_type_size = ggml_type_size(src1->type);
@@ -7029,6 +7054,7 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
     case GGML_OP_GET_ROWS:
     case GGML_OP_ADD:
     case GGML_OP_ACC:
+    case GGML_OP_SUB:
     case GGML_OP_MUL:
     case GGML_OP_DIV:
     case GGML_OP_CONCAT:
@@ -7083,6 +7109,7 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
         case GGML_OP_ACC:
         case GGML_OP_GET_ROWS:
         case GGML_OP_ADD:
+        case GGML_OP_SUB:
         case GGML_OP_MUL:
         case GGML_OP_DIV:
         case GGML_OP_CONCAT:
@@ -7139,6 +7166,10 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
     case GGML_OP_ADD:
         ggml_vk_add(ctx, compute_ctx, src0, src1, node, dryrun);
 
+        break;
+    case GGML_OP_SUB:
+        ggml_vk_sub(ctx, compute_ctx, src0, src1, node, dryrun);
+
         break;
     case GGML_OP_MUL:
         ggml_vk_mul(ctx, compute_ctx, src0, src1, node, dryrun);
@@ -7323,6 +7354,7 @@ static bool ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_tensor *
     case GGML_OP_ADD:
     case GGML_OP_ACC:
     case GGML_OP_GET_ROWS:
+    case GGML_OP_SUB:
     case GGML_OP_MUL:
     case GGML_OP_DIV:
     case GGML_OP_CONCAT:
@@ -8271,6 +8303,7 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
             return ggml_is_contiguous(op->src[0]);
         case GGML_OP_ADD:
         case GGML_OP_ACC:
+        case GGML_OP_SUB:
         case GGML_OP_MUL:
         case GGML_OP_DIV:
         case GGML_OP_CONCAT:
@@ -8762,6 +8795,8 @@ static void ggml_vk_check_results_0(ggml_tensor * tensor) {
         tensor_clone = ggml_mul_mat(ggml_ctx, src0_clone, src1_clone);
     } else if (tensor->op == GGML_OP_MUL_MAT_ID) {
         tensor_clone = ggml_mul_mat_id(ggml_ctx, src0_clone, src1_clone, src2_clone);
+    } else if (tensor->op == GGML_OP_SUB) {
+        tensor_clone = ggml_sub(ggml_ctx, src0_clone, src1_clone);
     } else if (tensor->op == GGML_OP_MUL) {
         tensor_clone = ggml_mul(ggml_ctx, src0_clone, src1_clone);
     } else if (tensor->op == GGML_OP_DIV) {

ggml/src/ggml-vulkan/vulkan-shaders/sub.comp

@@ -0,0 +1,29 @@
+#version 450
+
+#extension GL_EXT_shader_16bit_storage : require
+
+#include "types.comp"
+#include "generic_binary_head.comp"
+
+const uint num_threads = 256;
+
+layout(local_size_x = num_threads, local_size_y = 1, local_size_z = 1) in;
+
+void main() {
+    uint idx = get_idx();
+
+    // num_threads * num_iter must equal 512, to match the wg_denoms and get_idx calculation
+    const uint num_iter = 2;
+
+    [[unroll]] for (uint i = 0; i < num_iter; ++i) {
+        if (idx >= p.ne) {
+            continue;
+        }
+        uint i00, i01, i02, i03;
+        get_indices(idx, i00, i01, i02, i03);
+
+        data_d[get_doffset() + dst_idx(i00, i01, i02, i03)] = D_TYPE(FLOAT_TYPE(data_a[get_aoffset() + src0_idx(i00, i01, i02, i03)]) - FLOAT_TYPE(data_b[get_boffset() + src1_idx(i00, i01, i02, i03)]));
+
+        idx += num_threads;
+    }
+}

ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp

@@ -434,6 +434,8 @@ void process_shaders() {
     string_to_spv("add_f32", "add.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
     string_to_spv("add_f16_f32_f16", "add.comp", {{"A_TYPE", "float16_t"}, {"B_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"FLOAT_TYPE", "float"}});
 
+    string_to_spv("sub_f32", "sub.comp", {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}, {"FLOAT_TYPE", "float"}});
+
     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", {});

tests/test-backend-ops.cpp

@@ -1511,6 +1511,7 @@ struct test_cont : public test_case {
 };
 
 // GGML_OP_ADD
+// GGML_OP_SUB
 // GGML_OP_MUL
 // GGML_OP_DIV
 struct test_bin_bcast : public test_case {
@@ -3938,7 +3939,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
     test_cases.emplace_back(new test_cont(GGML_TYPE_BF16, {2, 3, 5 ,7}));
 
     auto add_test_bin_bcast = [&](ggml_type type, std::array<int64_t, 4> ne, std::array<int, 4> nr) {
-        for (auto op : {ggml_add, ggml_mul, ggml_div}) {
+        for (auto op : {ggml_add, ggml_sub, ggml_mul, ggml_div}) {
             test_cases.emplace_back(new test_bin_bcast(op, type, ne, nr));
         }
     };