perf: native ixformer decode (v1 ≤32K, v2 >32K) + flash_attn_varlen prefill

Replaces all Python PyTorch fallback attention with native ixformer kernels:

Decode path:
- ≤32K: paged_attention_v1 (5D KV layout, x=8) — verified on real BI-V100
- >32K: paged_attention_v2 (5D→4D permute) — verified 65K+ on real BI-V100
- Removes _forward_decode_pytorch Python fallback entirely

Prefill path (profiling):
- _run_sdpa_fallback now uses ixformer.flash_attn_varlen_func
- head_dim=256 verified correct (diff<0.004) and 1.7x faster than PyTorch
- Falls back to Q-tiling pure-math if ixformer unavailable

Also includes: MoE kernel integration, GDN C++ kernels, diagnostic scripts,
xllm upstream layer/kernel references, .dockerignore cleanup.

All changes verified on real BI-V100 hardware (single card).

ex_engine/xllm_models/llm/qwen3_5_mtp.h

@@ -0,0 +1,59 @@
+/* Copyright 2025-2026 The xLLM Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    https://github.com/jd-opensource/xllm/blob/main/LICENSE
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#pragma once
+
+#include <memory>
+
+#include "models/llm/qwen3_5.h"
+#include "models/llm/qwen3_5_mtp_base.h"
+#include "models/model_registry.h"
+
+namespace xllm {
+
+class Qwen3_5MtpModelImpl final : public Qwen3_5MtpModelImplBase {
+ public:
+  explicit Qwen3_5MtpModelImpl(const ModelContext& context)
+      : Qwen3_5MtpModelImplBase(context) {}
+};
+
+class Qwen3_5MtpForCausalLMImpl final : public Qwen3_5MtpForCausalLMImplBase {
+ public:
+  explicit Qwen3_5MtpForCausalLMImpl(const ModelContext& context)
+      : Qwen3_5MtpForCausalLMImplBase(
+            context,
+            std::make_shared<Qwen3_5MtpModelImpl>(context)) {}
+};
+TORCH_MODULE(Qwen3_5MtpForCausalLM);
+
+REGISTER_CAUSAL_MODEL(qwen3_5_mtp, Qwen3_5MtpForCausalLM);
+REGISTER_CAUSAL_MODEL(qwen3_5_moe_mtp, Qwen3_5MtpForCausalLM);
+
+REGISTER_MODEL_ARGS_LOADER(qwen3_5_mtp,
+                           [](const JsonReader& json, ModelArgs* args) {
+                             return qwen3_5_mtp::load_model_args(
+                                 json, args, "qwen3_5_text", "qwen3_5_mtp");
+                           });
+
+REGISTER_MODEL_ARGS_LOADER(qwen3_5_moe_mtp,
+                           [](const JsonReader& json, ModelArgs* args) {
+                             return qwen3_5_mtp::load_model_args(
+                                 json,
+                                 args,
+                                 "qwen3_5_moe_text",
+                                 "qwen3_5_moe_mtp");
+                           });
+
+}  // namespace xllm