/** Concat **/
struct ggml_webgpu_concat_pipeline_key {
- int type;
+ int type;
+ bool src_overlap;
- bool operator==(const ggml_webgpu_concat_pipeline_key & other) const { return type == other.type; }
+ bool operator==(const ggml_webgpu_concat_pipeline_key & other) const {
+ return type == other.type && src_overlap == other.src_overlap;
+ }
};
struct ggml_webgpu_concat_pipeline_key_hash {
size_t operator()(const ggml_webgpu_concat_pipeline_key & key) const {
size_t seed = 0;
ggml_webgpu_hash_combine(seed, key.type);
+ ggml_webgpu_hash_combine(seed, key.src_overlap);
return seed;
}
};
webgpu_pipeline get_concat_pipeline(const ggml_webgpu_shader_lib_context & context) {
ggml_webgpu_concat_pipeline_key key = {};
key.type = context.dst->type;
+ key.src_overlap = ggml_webgpu_tensor_overlap(context.src0, context.src1);
auto it = concat_pipelines.find(key);
if (it != concat_pipelines.end()) {
GGML_ABORT("Unsupported type for concat shader");
}
+ if (key.src_overlap) {
+ defines.push_back("SRC_OVERLAP");
+ variant += "_src_overlap";
+ }
+
defines.push_back(std::string("WG_SIZE=") + std::to_string(context.max_wg_size));
auto processed = preprocessor.preprocess(wgsl_concat, defines);
- auto decisions = std::make_shared<ggml_webgpu_generic_shader_decisions>();
+ auto decisions = std::make_shared<ggml_webgpu_binary_shader_decisions>();
decisions->wg_size = context.max_wg_size;
+ decisions->src_overlap = key.src_overlap;
webgpu_pipeline pipeline = ggml_webgpu_create_pipeline(device, processed, variant);
pipeline.context = decisions;
concat_pipelines[key] = pipeline;
uint32_t ne = (uint32_t) ggml_nelements(dst);
uint32_t dim = (uint32_t) dst->op_params[0];
- std::vector<uint32_t> params = {
- ne,
- (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src0) / ggml_type_size(src0->type)),
- (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src1) / ggml_type_size(src1->type)),
- (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)),
- (uint32_t) (src0->nb[0] / ggml_type_size(src0->type)),
- (uint32_t) (src0->nb[1] / ggml_type_size(src0->type)),
- (uint32_t) (src0->nb[2] / ggml_type_size(src0->type)),
- (uint32_t) (src0->nb[3] / ggml_type_size(src0->type)),
- (uint32_t) (src1->nb[0] / ggml_type_size(src1->type)),
- (uint32_t) (src1->nb[1] / ggml_type_size(src1->type)),
- (uint32_t) (src1->nb[2] / ggml_type_size(src1->type)),
- (uint32_t) (src1->nb[3] / ggml_type_size(src1->type)),
- (uint32_t) dst->ne[0],
- (uint32_t) dst->ne[1],
- (uint32_t) dst->ne[2],
- (uint32_t) dst->ne[3],
- dim,
- (uint32_t) src0->ne[dim]
- };
-
- std::vector<wgpu::BindGroupEntry> entries = {
- ggml_webgpu_make_tensor_bind_group_entry(ctx, 0, src0),
- ggml_webgpu_make_tensor_bind_group_entry(ctx, 1, src1),
- ggml_webgpu_make_tensor_bind_group_entry(ctx, 2, dst),
- };
-
ggml_webgpu_shader_lib_context shader_lib_ctx = {};
shader_lib_ctx.src0 = src0;
shader_lib_ctx.src1 = src1;
shader_lib_ctx.max_wg_size = ctx->global_ctx->capabilities.limits.maxComputeInvocationsPerWorkgroup;
webgpu_pipeline pipeline = ctx->shader_lib->get_concat_pipeline(shader_lib_ctx);
- auto * decisions = static_cast<ggml_webgpu_generic_shader_decisions *>(pipeline.context.get());
- uint32_t wg_x = CEIL_DIV(ne, decisions->wg_size);
+ auto * decisions = static_cast<ggml_webgpu_binary_shader_decisions *>(pipeline.context.get());
+
+ uint32_t offset_src0 = (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src0) / ggml_type_size(src0->type));
+ uint32_t offset_src1 = (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src1) / ggml_type_size(src1->type));
+ size_t merged_offset = 0;
+ size_t merged_size = 0;
+ if (decisions->src_overlap) {
+ const ggml_webgpu_merged_binding_range merged_range =
+ ggml_webgpu_tensor_merged_binding_range(ctx, { src0, src1 });
+ merged_offset = merged_range.offset;
+ merged_size = merged_range.size;
+ offset_src0 = ggml_webgpu_tensor_merged_element_offset(src0, merged_range);
+ offset_src1 = ggml_webgpu_tensor_merged_element_offset(src1, merged_range);
+ }
+
+ std::vector<uint32_t> params = { ne,
+ offset_src0,
+ offset_src1,
+ (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)),
+ (uint32_t) (src0->nb[0] / ggml_type_size(src0->type)),
+ (uint32_t) (src0->nb[1] / ggml_type_size(src0->type)),
+ (uint32_t) (src0->nb[2] / ggml_type_size(src0->type)),
+ (uint32_t) (src0->nb[3] / ggml_type_size(src0->type)),
+ (uint32_t) (src1->nb[0] / ggml_type_size(src1->type)),
+ (uint32_t) (src1->nb[1] / ggml_type_size(src1->type)),
+ (uint32_t) (src1->nb[2] / ggml_type_size(src1->type)),
+ (uint32_t) (src1->nb[3] / ggml_type_size(src1->type)),
+ (uint32_t) dst->ne[0],
+ (uint32_t) dst->ne[1],
+ (uint32_t) dst->ne[2],
+ (uint32_t) dst->ne[3],
+ dim,
+ (uint32_t) src0->ne[dim] };
+
+ std::vector<wgpu::BindGroupEntry> entries = {};
+ if (decisions->src_overlap) {
+ entries.push_back(
+ ggml_webgpu_make_bind_group_entry(0, ggml_webgpu_tensor_buf(src0), merged_offset, merged_size));
+ entries.push_back(ggml_webgpu_make_tensor_bind_group_entry(ctx, 1, dst));
+ } else {
+ entries.push_back(ggml_webgpu_make_tensor_bind_group_entry(ctx, 0, src0));
+ entries.push_back(ggml_webgpu_make_tensor_bind_group_entry(ctx, 1, src1));
+ entries.push_back(ggml_webgpu_make_tensor_bind_group_entry(ctx, 2, dst));
+ }
+
+ uint32_t wg_x = CEIL_DIV(ne, decisions->wg_size);
return ggml_backend_webgpu_build(ctx, pipeline, params, entries, wg_x);
}
#define DataType i32
#endif
+#ifdef SRC_OVERLAP
+@group(0) @binding(0)
+var<storage, read_write> merged_src: array<DataType>;
+
+@group(0) @binding(1)
+var<storage, read_write> dst: array<DataType>;
+
+@group(0) @binding(2)
+var<uniform> params: Params;
+#else
@group(0) @binding(0)
var<storage, read_write> src0: array<DataType>;
@group(0) @binding(3)
var<uniform> params: Params;
-
+#endif
@compute @workgroup_size(WG_SIZE)
fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
ni[1] * params.stride_src0_1 +
ni[2] * params.stride_src0_2 +
ni[3] * params.stride_src0_3;
+#ifdef SRC_OVERLAP
+ dst[params.offset_dst + gid.x] = merged_src[params.offset_src0 + src_i];
+#else
dst[params.offset_dst + gid.x] = src0[params.offset_src0 + src_i];
+#endif
} else {
ni[params.dim] -= params.src0_nedim;
let src_i = ni[0] * params.stride_src1_0 +
ni[1] * params.stride_src1_1 +
ni[2] * params.stride_src1_2 +
ni[3] * params.stride_src1_3;
+#ifdef SRC_OVERLAP
+ dst[params.offset_dst + gid.x] = merged_src[params.offset_src1 + src_i];
+#else
dst[params.offset_dst + gid.x] = src1[params.offset_src1 + src_i];
+#endif
}
}
}