Get addition and multiplication working

ggml/src/ggml-webgpu/ggml-webgpu.cpp

@@ -126,6 +126,9 @@ struct webgpu_context_struct {
     wgpu::ComputePipeline set_rows_pipeline;
     wgpu::ComputePipeline cpy_pipeline;
     wgpu::ComputePipeline add_pipeline[2];
+    wgpu::ComputePipeline add_ip_pipeline[2];
+    wgpu::ComputePipeline mul_pipeline[2];
+    wgpu::ComputePipeline mul_ip_pipeline[2];
 
     size_t memset_bytes_per_thread;
 
@@ -347,6 +350,7 @@ static void ggml_backend_webgpu_build_and_enqueue(webgpu_context &
                                                   std::vector<uint32_t>             params,
                                                   std::vector<wgpu::BindGroupEntry> bind_group_entries,
                                                   uint32_t                          wg_x,
+                                                  const char *                      bind_group_label = nullptr,
                                                   bool                              submit_and_wait  = false) {
     webgpu_pool_bufs params_bufs = ctx->param_buf_pool.alloc_bufs();
 
@@ -368,6 +372,9 @@ static void ggml_backend_webgpu_build_and_enqueue(webgpu_context &
     bind_group_desc.layout     = pipeline.GetBindGroupLayout(0);
     bind_group_desc.entryCount = bind_group_entries.size();
     bind_group_desc.entries    = bind_group_entries.data();
+    if (bind_group_label) {
+        bind_group_desc.label = bind_group_label;
+    }
     wgpu::BindGroup bind_group = ctx->device.CreateBindGroup(&bind_group_desc);
 
     wgpu::CommandEncoder encoder = ctx->device.CreateCommandEncoder();
@@ -413,7 +420,7 @@ static void ggml_backend_webgpu_buffer_memset(webgpu_context & ctx,
     };
     size_t   bytes_per_wg = ctx->limits.maxComputeWorkgroupSizeX * ctx->memset_bytes_per_thread;
     uint32_t wg_x         = ((size + 3) + bytes_per_wg - 1) / bytes_per_wg;
-    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->memset_pipeline, params, entries, wg_x, true);
+    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->memset_pipeline, params, entries, wg_x, "MEMSET", true);
 }
 
 /** End WebGPU Actions */
@@ -457,6 +464,12 @@ static size_t ggml_webgpu_tensor_binding_size(webgpu_context & ctx, ggml_tensor
            ~(WEBGPU_STORAGE_BUF_BINDING_MULT - 1);
 }
 
+// Used to determine if two tensors are the same for in-place operations
+static bool ggml_webgpu_tensor_equal(ggml_tensor * a, ggml_tensor * b) {
+    return (ggml_webgpu_tensor_buf(a).Get() == ggml_webgpu_tensor_buf(b).Get()) &&
+           (ggml_webgpu_tensor_offset(a) == ggml_webgpu_tensor_offset(b));
+}
+
 static void ggml_webgpu_cpy(webgpu_context & ctx, ggml_tensor * src, ggml_tensor * dst) {
     uint32_t ne = (uint32_t) ggml_nelements(dst);
 
@@ -485,7 +498,7 @@ static void ggml_webgpu_cpy(webgpu_context & ctx, ggml_tensor * src, ggml_tensor
 
     size_t   max_wg_size = ctx->limits.maxComputeWorkgroupSizeX;
     uint32_t wg_x        = (ne + max_wg_size - 1) / max_wg_size;
-    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->cpy_pipeline, params, entries, wg_x);
+    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->cpy_pipeline, params, entries, wg_x, ggml_op_name(dst->op));
 }
 
 static void ggml_webgpu_set_rows(webgpu_context & ctx, ggml_tensor * src, ggml_tensor * idx, ggml_tensor * dst) {
@@ -537,7 +550,7 @@ static void ggml_webgpu_set_rows(webgpu_context & ctx, ggml_tensor * src, ggml_t
     std::lock_guard<std::recursive_mutex> lock(ctx->mutex);
     ctx->staged_set_row_error_bufs.push_back(error_bufs);
 
-    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->set_rows_pipeline, params, entries, wg_x);
+    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->set_rows_pipeline, params, entries, wg_x, ggml_op_name(dst->op));
 }
 
 static void ggml_webgpu_mul_mat(webgpu_context & ctx, ggml_tensor * src0, ggml_tensor * src1, ggml_tensor * dst) {
@@ -577,10 +590,16 @@ static void ggml_webgpu_mul_mat(webgpu_context & ctx, ggml_tensor * src0, ggml_t
 
     uint32_t wg_x =
         (dst->ne[0] * dst->ne[1] * dst->ne[2] * dst->ne[3] + WEBGPU_MUL_MAT_WG_SIZE - 1) / WEBGPU_MUL_MAT_WG_SIZE;
-    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->mul_mat_pipeline[src0->type][src1->type], params, entries, wg_x);
+    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->mul_mat_pipeline[src0->type][src1->type], params, entries, wg_x,
+                                          ggml_op_name(dst->op));
 }
 
-static void ggml_webgpu_add(webgpu_context & ctx, ggml_tensor * src0, ggml_tensor * src1, ggml_tensor * dst) {
+static void ggml_webgpu_binary_op(webgpu_context &        ctx,
+                                  ggml_tensor *           src0,
+                                  ggml_tensor *           src1,
+                                  ggml_tensor *           dst,
+                                  wgpu::ComputePipeline & pipeline,
+                                  bool                    in_place) {
     std::vector<uint32_t> params = {
         (uint32_t) ggml_nelements(dst),
         (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src0) / ggml_type_size(src0->type)),
@@ -607,16 +626,18 @@ static void ggml_webgpu_add(webgpu_context & ctx, ggml_tensor * src0, ggml_tenso
         { .binding = 1,
          .buffer  = ggml_webgpu_tensor_buf(src1),
          .offset  = ggml_webgpu_tensor_align_offset(ctx, src1),
-         .size    = ggml_webgpu_tensor_binding_size(ctx, src1) },
+         .size    = ggml_webgpu_tensor_binding_size(ctx, src1) }
-        { .binding = 2,
+    };
+    if (!in_place) {
+        entries.push_back({ .binding = 2,
                             .buffer  = ggml_webgpu_tensor_buf(dst),
                             .offset  = ggml_webgpu_tensor_align_offset(ctx, dst),
-         .size    = ggml_webgpu_tensor_binding_size(ctx, dst)  }
+                            .size    = ggml_webgpu_tensor_binding_size(ctx, dst) });
-    };
+    }
 
     size_t   max_wg_size = ctx->limits.maxComputeWorkgroupSizeX;
     uint32_t wg_x        = (ggml_nelements(dst) + max_wg_size - 1) / max_wg_size;
-    ggml_backend_webgpu_build_and_enqueue(ctx, ctx->add_pipeline[dst->type], params, entries, wg_x);
+    ggml_backend_webgpu_build_and_enqueue(ctx, pipeline, params, entries, wg_x, ggml_op_name(dst->op));
 }
 
 // Returns true if node has enqueued work into the queue, false otherwise
@@ -654,7 +675,20 @@ static bool ggml_webgpu_encode_node(webgpu_context ctx, ggml_tensor * node) {
             }
         case GGML_OP_ADD:
             {
-                ggml_webgpu_add(ctx, src0, src1, node);
+                if (ggml_webgpu_tensor_equal(src0, node)) {
+                    ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->add_ip_pipeline[node->type], true);
+                } else {
+                    ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->add_pipeline[node->type], false);
+                }
+                break;
+            }
+        case GGML_OP_MUL:
+            {
+                if (ggml_webgpu_tensor_equal(src0, node)) {
+                    ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->mul_ip_pipeline[node->type], true);
+                } else {
+                    ggml_webgpu_binary_op(ctx, src0, src1, node, ctx->mul_pipeline[node->type], false);
+                }
                 break;
             }
         default:
@@ -994,8 +1028,28 @@ static void ggml_webgpu_init_add_pipeline(webgpu_context & webgpu_ctx) {
     std::vector<wgpu::ConstantEntry> constants(1);
     constants[0].key   = "wg_size";
     constants[0].value = webgpu_ctx->limits.maxComputeWorkgroupSizeX;
-    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F32], wgsl_add_f32, "add_f32", constants);
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F32], wgsl_add_f32, "add_f32",
-    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F16], wgsl_add_f16, "add_f16", constants);
+                                constants);
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_pipeline[GGML_TYPE_F16], wgsl_add_f16, "add_f16",
+                                constants);
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_ip_pipeline[GGML_TYPE_F32], wgsl_add_in_place_f32,
+                                "add_in_place_f32", constants);
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->add_ip_pipeline[GGML_TYPE_F16], wgsl_add_in_place_f16,
+                                "add_in_place_f16", constants);
+}
+
+static void ggml_webgpu_init_mul_pipeline(webgpu_context & webgpu_ctx) {
+    std::vector<wgpu::ConstantEntry> constants(1);
+    constants[0].key   = "wg_size";
+    constants[0].value = webgpu_ctx->limits.maxComputeWorkgroupSizeX;
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F32], wgsl_mul_f32, "mul_f32",
+                                constants);
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_pipeline[GGML_TYPE_F16], wgsl_mul_f16, "mul_f16",
+                                constants);
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_ip_pipeline[GGML_TYPE_F32], wgsl_mul_in_place_f32,
+                                "mul_in_place_f32", constants);
+    ggml_webgpu_create_pipeline(webgpu_ctx->device, webgpu_ctx->mul_ip_pipeline[GGML_TYPE_F16], wgsl_mul_in_place_f16,
+                                "mul_in_place_f16", constants);
 }
 
 static ggml_backend_t ggml_backend_webgpu_device_init(ggml_backend_dev_t dev, const char * params) {
@@ -1048,22 +1102,30 @@ static bool ggml_backend_webgpu_device_supports_buft(ggml_backend_dev_t dev, ggm
 static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const ggml_tensor * op) {
     GGML_UNUSED(dev);
 
+    bool supports_op = false;
     switch (op->op) {
         case GGML_OP_NONE:
         case GGML_OP_VIEW:
         case GGML_OP_PERMUTE:
         case GGML_OP_TRANSPOSE:
         case GGML_OP_RESHAPE:
+            supports_op = true;
+            break;
         case GGML_OP_ADD:
-            return true;
+        case GGML_OP_MUL:
+            supports_op = (op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16) && (op->src[0]->type == op->type) &&
+                          (op->src[1]->type == op->type);
+            break;
         case GGML_OP_CPY:
         case GGML_OP_SET_ROWS:
-            return op->type == GGML_TYPE_F16 && op->src[0]->type == GGML_TYPE_F32;
+            supports_op = (op->type == GGML_TYPE_F16 && op->src[0]->type == GGML_TYPE_F32);
+            break;
         case GGML_OP_MUL_MAT:
             {
                 switch (op->src[1]->type) {
                     case GGML_TYPE_F16:
-                        return op->src[0]->type == GGML_TYPE_F16;
+                        supports_op = (op->src[0]->type == GGML_TYPE_F16);
+                        break;
                     case GGML_TYPE_F32:
                         switch (op->src[0]->type) {
                             case GGML_TYPE_F32:
@@ -1087,17 +1149,26 @@ static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const
                             case GGML_TYPE_IQ1_M:
                             case GGML_TYPE_IQ4_NL:
                             case GGML_TYPE_IQ4_XS:
-                                return true;
+                                supports_op = true;
+                                break;
                             default:
-                                return false;
+                                break;
                         }
                     default:
-                        return false;
+                        break;
                 }
             }
         default:
-            return false;
+            break;
     }
+#ifdef GGML_WEBGPU_DEBUG
+    if (!supports_op) {
+        WEBGPU_LOG_DEBUG("not supported: " << ggml_op_name(op->op) << " with types dst: " << ggml_type_name(op->type)
+                                           << ", src0: " << (op->src[0] ? ggml_type_name(op->src[0]->type) : "null")
+                                           << ", src1: " << (op->src[1] ? ggml_type_name(op->src[1]->type) : "null"));
+    }
+#endif
+    return supports_op;
 }
 
 static struct ggml_backend_device_i ggml_backend_webgpu_device_i = {
@@ -1210,6 +1281,7 @@ static ggml_backend_dev_t ggml_backend_webgpu_reg_get_device(ggml_backend_reg_t
     ggml_webgpu_init_set_rows_pipeline(ctx);
     ggml_webgpu_init_cpy_pipeline(ctx);
     ggml_webgpu_init_add_pipeline(ctx);
+    ggml_webgpu_init_mul_pipeline(ctx);
 
 #ifdef GGML_WEBGPU_DEBUG
     // Initialize debug buffers

ggml/src/ggml-webgpu/wgsl-shaders/add.tmpl.wgsl

@@ -19,6 +19,8 @@
 
 enable f16;
 
+#include "binary_head.tmpl"
+
 @group(0) @binding(0)
 var<storage, read_write> src0: array<{{TYPE}}>;
 
@@ -28,71 +30,15 @@ var<storage, read_write> src1: array<{{TYPE}}>;
 @group(0) @binding(2)
 var<storage, read_write> dst: array<{{TYPE}}>;
 
-struct Params {
-    ne: u32,
-
-    // offsets in elements
-    offset_src0: u32,
-    offset_src1: u32,
-    offset_dst: u32,
-
-    stride_src1_0: u32,
-    stride_src1_1: u32,
-    stride_src1_2: u32,
-    stride_src1_3: u32,
-
-    a_ne0: u32,
-    a_ne1: u32,
-    a_ne2: u32,
-
-    b_ne0: u32,
-    b_ne1: u32,
-    b_ne2: u32,
-    b_ne3: u32,
-};
-
 @group(0) @binding(3)
 var<uniform> params: Params;
 
 override wg_size: u32;
 @compute @workgroup_size(wg_size)
 fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
-    if (gid.x >= params.ne) {
+    if (gid.x < params.ne) {
-        return;
+        dst[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] + src1[params.offset_src1 + src1_index(gid.x)];
     }
-
-    // i = thread id, ranges from 0 --> total ne - 1
-    // represents the position in the flat array a we are adding with array b
-    var i = gid.x;
-
-    // given the index of linear a, we want to compute the 4d index [a_i0, a_i1, a_i2, a_i3]
-    // we need this because tensor a and b are different shapes
-    // so the same linear index won't work for b, and we can only compute b's linear index from the 4d index of a
-
-    let a_i3 = i / (params.a_ne2 * params.a_ne1 * params.a_ne0);
-    i = i % (params.a_ne2 * params.a_ne1 * params.a_ne0);
-    let a_i2 = i / (params.a_ne1 * params.a_ne0);
-    i = i % (params.a_ne1 * params.a_ne0);
-    let a_i1 = i / params.a_ne0;
-    let a_i0 = i % params.a_ne0;
-
-    // handle repetition of b
-    // index loops back to the beginning and repeats after elements are exhausted = modulo
-    let b_i0 = a_i0 % params.b_ne0;
-    let b_i1 = a_i1 % params.b_ne1;
-    let b_i2 = a_i2 % params.b_ne2;
-    let b_i3 = a_i3 % params.b_ne3;
-
-    // compute index for position in b's flat array
-    let src1_idx = b_i0 * params.stride_src1_0 +
-                b_i1 * params.stride_src1_1 +
-                b_i2 * params.stride_src1_2 +
-                b_i3 * params.stride_src1_3;
-
-    // actual addition operation, now that the indexes are all figured out
-    // ensuring that the offsets are included
-    // gid.x used for flat indexing into dst and a, since variable i was modified during calcs
-    dst[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] + src1[params.offset_src1 + src1_idx];
 }
 
 #end(SHADER)

ggml/src/ggml-webgpu/wgsl-shaders/add_in_place.tmpl.wgsl

@@ -0,0 +1,41 @@
+#define(VARIANTS)
+
+[
+  {
+    "REPLS": {
+      "TYPE" : "f32",
+    }
+  },
+  {
+    "REPLS": {
+      "TYPE" : "f16",
+    }
+  }
+]
+
+#end(VARIANTS)
+
+#define(SHADER)
+
+enable f16;
+
+#include "binary_head.tmpl"
+
+@group(0) @binding(0)
+var<storage, read_write> src0: array<{{TYPE}}>;
+
+@group(0) @binding(1)
+var<storage, read_write> src1: array<{{TYPE}}>;
+
+@group(0) @binding(2)
+var<uniform> params: Params;
+
+override wg_size: u32;
+@compute @workgroup_size(wg_size)
+fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
+    if (gid.x < params.ne) {
+        src0[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] + src1[params.offset_src1 + src1_index(gid.x)];
+    }
+}
+
+#end(SHADER)

ggml/src/ggml-webgpu/wgsl-shaders/binary_head.tmpl

@@ -0,0 +1,45 @@
+struct Params {
+    ne: u32,
+
+    // offsets in elements
+    offset_src0: u32,
+    offset_src1: u32,
+    offset_dst: u32,
+
+    stride_src1_0: u32,
+    stride_src1_1: u32,
+    stride_src1_2: u32,
+    stride_src1_3: u32,
+
+    a_ne0: u32,
+    a_ne1: u32,
+    a_ne2: u32,
+
+    b_ne0: u32,
+    b_ne1: u32,
+    b_ne2: u32,
+    b_ne3: u32,
+};
+
+fn src1_index(_i: u32) -> u32 {
+    var i = _i;
+    let a_i3 = i / (params.a_ne2 * params.a_ne1 * params.a_ne0);
+    i = i % (params.a_ne2 * params.a_ne1 * params.a_ne0);
+    let a_i2 = i / (params.a_ne1 * params.a_ne0);
+    i = i % (params.a_ne1 * params.a_ne0);
+    let a_i1 = i / params.a_ne0;
+    let a_i0 = i % params.a_ne0;
+
+    // handle repetition of b
+    // index loops back to the beginning and repeats after elements are exhausted = modulo
+    let b_i0 = a_i0 % params.b_ne0;
+    let b_i1 = a_i1 % params.b_ne1;
+    let b_i2 = a_i2 % params.b_ne2;
+    let b_i3 = a_i3 % params.b_ne3;
+
+    // compute index for position in b's flat array
+    return b_i0 * params.stride_src1_0 +
+           b_i1 * params.stride_src1_1 +
+           b_i2 * params.stride_src1_2 +
+           b_i3 * params.stride_src1_3;
+}

ggml/src/ggml-webgpu/wgsl-shaders/embed_wgsl.py

@@ -26,6 +26,24 @@ def replace_placeholders(shader_text, replacements):
         shader_text = re.sub(pattern, str(val), shader_text)
     return shader_text
 
+def expand_includes(shader, input_dir):
+    """
+    Replace #include "file" lines in the text with the contents of that file.
+    Searches for files relative to input_dir.
+    """
+    include_pattern = re.compile(r'^\s*#include\s+"([^"]+)"\s*$', re.MULTILINE)
+
+    def replacer(match):
+        fname = match.group(1)
+        file_path = os.path.join(input_dir, fname)
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"Included file not found: {file_path}")
+        with open(file_path, "r", encoding="utf-8") as f:
+            included_code = f.read()
+        # Recursively expand includes inside the included file
+        return expand_includes(included_code, input_dir)
+
+    return include_pattern.sub(replacer, shader)
 
 def write_shader(shader_name, shader_code, output_dir, outfile):
     if output_dir:
@@ -35,8 +53,9 @@ def write_shader(shader_name, shader_code, output_dir, outfile):
     outfile.write(f'const char* wgsl_{shader_name} = R"({shader_code})";\n\n')
 
 
-def generate_variants(shader_path, output_dir, outfile):
+def generate_variants(fname, input_dir, output_dir, outfile):
-    shader_base_name = shader_path.split("/")[-1].split(".")[0]
+    shader_path = os.path.join(input_dir, fname)
+    shader_base_name = fname.split(".")[0]
 
     with open(shader_path, "r", encoding="utf-8") as f:
         text = f.read()
@@ -52,6 +71,7 @@ def generate_variants(shader_path, output_dir, outfile):
             decls_map = {}
 
         shader_template = extract_block(text, "SHADER")
+        shader_template = expand_includes(shader_template, input_dir)
         for variant in variants:
             if "DECLS" in variant:
                 decls = variant["DECLS"]
@@ -89,7 +109,7 @@ def main():
         out.write("// Auto-generated shader embedding\n\n")
         for fname in sorted(os.listdir(args.input_dir)):
             if fname.endswith(".wgsl"):
-                generate_variants(os.path.join(args.input_dir, fname), args.output_dir, out)
+                generate_variants(fname, args.input_dir, args.output_dir, out)
 
 
 if __name__ == "__main__":

ggml/src/ggml-webgpu/wgsl-shaders/mul.tmpl.wgsl

@@ -0,0 +1,44 @@
+#define(VARIANTS)
+
+[
+  {
+    "REPLS": {
+      "TYPE" : "f32",
+    }
+  },
+  {
+    "REPLS": {
+      "TYPE" : "f16",
+    }
+  }
+]
+
+#end(VARIANTS)
+
+#define(SHADER)
+
+enable f16;
+
+#include "binary_head.tmpl"
+
+@group(0) @binding(0)
+var<storage, read_write> src0: array<{{TYPE}}>;
+
+@group(0) @binding(1)
+var<storage, read_write> src1: array<{{TYPE}}>;
+
+@group(0) @binding(2)
+var<storage, read_write> dst: array<{{TYPE}}>;
+
+@group(0) @binding(3)
+var<uniform> params: Params;
+
+override wg_size: u32;
+@compute @workgroup_size(wg_size)
+fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
+    if (gid.x < params.ne) {
+        dst[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] * src1[params.offset_src1 + src1_index(gid.x)];
+    }
+}
+
+#end(SHADER)

ggml/src/ggml-webgpu/wgsl-shaders/mul_in_place.tmpl.wgsl

@@ -0,0 +1,41 @@
+#define(VARIANTS)
+
+[
+  {
+    "REPLS": {
+      "TYPE" : "f32",
+    }
+  },
+  {
+    "REPLS": {
+      "TYPE" : "f16",
+    }
+  }
+]
+
+#end(VARIANTS)
+
+#define(SHADER)
+
+enable f16;
+
+#include "binary_head.tmpl"
+
+@group(0) @binding(0)
+var<storage, read_write> src0: array<{{TYPE}}>;
+
+@group(0) @binding(1)
+var<storage, read_write> src1: array<{{TYPE}}>;
+
+@group(0) @binding(2)
+var<uniform> params: Params;
+
+override wg_size: u32;
+@compute @workgroup_size(wg_size)
+fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
+    if (gid.x < params.ne) {
+        src0[params.offset_dst + gid.x] = src0[params.offset_src0 + gid.x] * src1[params.offset_src1 + src1_index(gid.x)];
+    }
+}
+
+#end(SHADER)