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@@ -353,6 +353,7 @@ struct vk_device_struct {
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vk_pipeline pipeline_flash_attn_f32_f16_D112[GGML_TYPE_COUNT][2][2][2];
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vk_pipeline pipeline_flash_attn_f32_f16_D128[GGML_TYPE_COUNT][2][2][2];
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vk_pipeline pipeline_flash_attn_f32_f16_D256[GGML_TYPE_COUNT][2][2][2];
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+ vk_pipeline pipeline_flash_attn_split_k_reduce;
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std::unordered_map<std::string, vk_pipeline_ref> pipelines;
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std::unordered_map<std::string, uint64_t> pipeline_descriptor_set_requirements;
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@@ -504,6 +505,8 @@ struct vk_flash_attn_push_constants {
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float m1;
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uint32_t gqa_ratio;
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+ uint32_t split_kv;
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+ uint32_t k_num;
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};
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struct vk_op_push_constants {
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@@ -1476,7 +1479,7 @@ static std::array<uint32_t, 2> fa_rows_cols(uint32_t D, uint32_t clamp, ggml_typ
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// small rows, large cols
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if (small_rows) {
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- return {flash_attention_num_small_rows, 128};
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+ return {flash_attention_num_small_rows, 64};
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}
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// small cols to reduce register count
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if (ggml_is_quantized(type) || D == 256) {
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@@ -2332,6 +2335,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
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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);
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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);
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+ ggml_vk_create_pipeline(device, device->pipeline_flash_attn_split_k_reduce, "fa_split_k_reduce", fa_split_k_reduce_len, fa_split_k_reduce_data, "main", 2, 3 * sizeof(uint32_t), {1, 1, 1}, {}, 1, true);
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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);
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for (uint32_t i = 0; i < p021_max_gqa_ratio; ++i) {
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@@ -5479,9 +5483,38 @@ static void ggml_vk_flash_attn(ggml_backend_vk_context * ctx, vk_context& subctx
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workgroups_y /= N;
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}
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+ uint32_t split_kv = KV;
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+ uint32_t split_k = 1;
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+
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+ if (gqa_ratio > 1 && ctx->device->shader_core_count > 0) {
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+ GGML_ASSERT(workgroups_x == 1);
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+ // Try to run two workgroups per SM.
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+ split_k = ctx->device->shader_core_count * 2 / workgroups_y;
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+ if (split_k > 1) {
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+ // Try to evenly split KV into split_k chunks, but it needs to be a multiple
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+ // of "align", so recompute split_k based on that.
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+ split_kv = ROUNDUP_POW2(KV / split_k, pipelines[1]->align);
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+ split_k = CEIL_DIV(KV, split_kv);
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+ workgroups_x = split_k;
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+ }
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+ }
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+
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+ // Reserve space for split_k temporaries. For each split, we need to store the O matrix (D x ne1)
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+ // and the per-row m and L values (ne1 rows).
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+ const uint64_t split_k_size = split_k > 1 ? (D * ne1 * sizeof(float) + ne1 * sizeof(float) * 2) * split_k : 0;
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+ if (split_k_size > ctx->device->max_memory_allocation_size) {
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+ GGML_ABORT("Requested preallocation size is too large");
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+ }
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+ if (ctx->prealloc_size_split_k < split_k_size) {
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+ ctx->prealloc_size_split_k = split_k_size;
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+ }
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+
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if (dryrun) {
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// Request descriptor sets
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ggml_pipeline_request_descriptor_sets(ctx->device, pipeline, 1);
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+ if (split_k > 1) {
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+ ggml_pipeline_request_descriptor_sets(ctx->device, ctx->device->pipeline_flash_attn_split_k_reduce, 1);
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+ }
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return;
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}
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@@ -5502,8 +5535,6 @@ static void ggml_vk_flash_attn(ggml_backend_vk_context * ctx, vk_context& subctx
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const float m0 = powf(2.0f, -(max_bias ) / n_head_log2);
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const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
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- ggml_vk_sync_buffers(subctx);
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-
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vk_buffer d_Q = nullptr, d_K = nullptr, d_V = nullptr, d_D = nullptr, d_M = nullptr;
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size_t q_buf_offset = 0, k_buf_offset = 0, v_buf_offset = 0, d_buf_offset = 0, m_buf_offset = 0;
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@@ -5568,16 +5599,45 @@ static void ggml_vk_flash_attn(ggml_backend_vk_context * ctx, vk_context& subctx
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v_stride, (uint32_t)nbv2, (uint32_t)nbv3,
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nbm1,
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scale, max_bias, logit_softcap,
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- mask != nullptr, n_head_log2, m0, m1, gqa_ratio };
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- ggml_vk_dispatch_pipeline(ctx, subctx, pipeline,
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- {
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- vk_subbuffer{d_Q, q_buf_offset, VK_WHOLE_SIZE},
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- vk_subbuffer{d_K, k_buf_offset, VK_WHOLE_SIZE},
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- vk_subbuffer{d_V, v_buf_offset, VK_WHOLE_SIZE},
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- vk_subbuffer{d_M, m_buf_offset, VK_WHOLE_SIZE},
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- vk_subbuffer{d_D, d_buf_offset, VK_WHOLE_SIZE},
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- },
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- sizeof(vk_flash_attn_push_constants), &pc, { workgroups_x, workgroups_y, workgroups_z });
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+ mask != nullptr, n_head_log2, m0, m1,
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+ gqa_ratio, split_kv, split_k };
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+
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+ ggml_vk_sync_buffers(subctx);
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+
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+ if (split_k > 1) {
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+ ggml_vk_dispatch_pipeline(ctx, subctx, pipeline,
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+ {
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+ vk_subbuffer{d_Q, q_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_K, k_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_V, v_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_M, m_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{ctx->prealloc_split_k, 0, VK_WHOLE_SIZE},
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+ },
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+ // We only use split_k when group query attention is enabled, which means
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+ // there's no more than one tile of rows (i.e. workgroups_x would have been
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+ // one). We reuse workgroups_x to mean the number of splits, so we need to
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+ // cancel out the divide by wg_denoms[0].
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+ sizeof(vk_flash_attn_push_constants), &pc, { workgroups_x * pipeline->wg_denoms[0], workgroups_y, workgroups_z });
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+
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+ ggml_vk_sync_buffers(subctx);
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+ const std::array<uint32_t, 3> pc2 = { D, (uint32_t)ne1, split_k };
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+ ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_flash_attn_split_k_reduce,
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+ {
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+ vk_subbuffer{ctx->prealloc_split_k, 0, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_D, d_buf_offset, VK_WHOLE_SIZE},
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+ },
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+ pc2.size() * uint32_t{sizeof(uint32_t)}, pc2.data(), { (uint32_t)ne1, 1, 1 });
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+ } else {
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+ ggml_vk_dispatch_pipeline(ctx, subctx, pipeline,
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+ {
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+ vk_subbuffer{d_Q, q_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_K, k_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_V, v_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_M, m_buf_offset, VK_WHOLE_SIZE},
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+ vk_subbuffer{d_D, d_buf_offset, VK_WHOLE_SIZE},
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+ },
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+ sizeof(vk_flash_attn_push_constants), &pc, { workgroups_x, workgroups_y, workgroups_z });
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+ }
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}
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static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, ggml_op op) {
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