feat: import CUDA kernels from xllm/CCCL/FLA upstream repos

Sources cloned and tree'd (no --depth):
  - jd-opensource/xllm: ILU kernels, CUDA kernels, MoE kernels
  - NVIDIA/cccl: CUB tuning/dispatch headers (block-level primitives)
  - fla-org/flash-linear-attention: Triton GDN kernels
  - NVIDIA/cutlass: grouped GEMM reference (read, not copied)
  - Dao-AILab/flash-attention: attention kernel reference (SM80+, read only)

New CUDA kernels (from xllm, SM-agnostic, portable to BI-V100):
  ex_engine/xllm_kernels/cuda/activation.cu    (188 lines) — silu_and_mul, gelu
  ex_engine/xllm_kernels/cuda/norm.cu          (600 lines) — rms_norm, fused_add_rms_norm
  ex_engine/xllm_kernels/cuda/rope.cu          (258 lines) — rotary_embedding
  ex_engine/xllm_kernels/cuda/block_copy.cu    (209 lines) — copy_blocks, swap_blocks
  ex_engine/xllm_kernels/cuda/reshape_paged_cache.cu (101 lines) — KV cache ops
  ex_engine/xllm_kernels/cuda/headers/         (5 headers for compilation)

ILU bridge kernel sources (from xllm, verified SAME as upstream):
  ex_engine/xllm_kernels/ilu/    (10 files, 925 lines total)
  — activation.cpp, attention.cpp, fused_moe.cpp, group_gemm.cpp,
    matmul.cpp, norm.cpp, rope.cpp, ilu_ops_api.h, ixformer.h, utils.h

FLA Triton GDN kernels (for GatedDeltaNet without SM90+ FlashQLA):
  ex_engine/fla_kernels/gated_delta_rule/  (7 files, 2370 lines)
  — chunk_fwd.py (428), chunk.py (487), wy_fast.py (409),
    fused_recurrent.py (392), naive.py (161), gate.py (380)

CCCL sync (12 tuning + 14 dispatch headers updated from NVIDIA/cccl):
  cccl_upstream/cub/cub/device/dispatch/tuning/ — 12 changed files synced
  cccl_upstream/cub/cub/device/dispatch/ — 14 changed dispatch files synced

Compilation targets for real machine (ivcore10):
  1. CUDA kernels: --cuda-gpu-arch=ivcore10 via corex clang/16
  2. ILU bridges: torch.utils.cpp_extension linking ixformer .so
  3. FLA kernels: Triton JIT (if Triton works on BI-V100)

ex_engine/xllm_kernels/ilu/utils.h

@@ -0,0 +1,63 @@
+/* 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
+namespace xllm::kernel::ilu {
+#undef check_tensor_contiguous
+#define check_tensor_contiguous(x, type) \
+  TORCH_CHECK(x.scalar_type() == type);  \
+  TORCH_CHECK(x.is_cuda());              \
+  TORCH_CHECK(x.is_contiguous());
+
+#undef check_tensor_half_bf_float
+#define check_tensor_half_bf_float(x)                       \
+  TORCH_CHECK(x.scalar_type() == at::ScalarType::Half ||    \
+              x.scalar_type() == at::ScalarType::Float ||   \
+              x.scalar_type() == at::ScalarType::BFloat16); \
+  TORCH_CHECK(x.is_cuda());
+
+// from torchCheckMsgImpl
+inline const char* ixformer_check_msg_impl(const char* msg) { return msg; }
+// // If there is just 1 user-provided C-string argument, use it.
+
+#define IXFORMER_CHECK_MSG(cond, type, ...)                 \
+  (ixformer_check_msg_impl(                                 \
+      "Expected " #cond                                     \
+      " to be true, but got false.  "                       \
+      "(Could this error message be improved?  If so, "     \
+      "please report an enhancement request to ixformer.)", \
+      ##__VA_ARGS__))
+
+#define IXFORMER_CHECK(cond, ...)                                            \
+  {                                                                          \
+    if (!(cond)) {                                                           \
+      std::cerr << __FILE__ << " (" << __LINE__ << ")"                       \
+                << "-" << __FUNCTION__ << " : "                              \
+                << IXFORMER_CHECK_MSG(cond, "", ##__VA_ARGS__) << std::endl; \
+      throw std::runtime_error("IXFORMER_CHECK ERROR");                      \
+    }                                                                        \
+  }
+
+#undef CUINFER_CHECK
+#define CUINFER_CHECK(func)                                                \
+  do {                                                                     \
+    cuinferStatus_t status = (func);                                       \
+    if (status != CUINFER_STATUS_SUCCESS) {                                \
+      std::cerr << "Error in file " << __FILE__ << " on line " << __LINE__ \
+                << ": " << cuinferGetErrorString(status) << std::endl;     \
+      throw std::runtime_error("CUINFER_CHECK ERROR");                     \
+    }                                                                      \
+  } while (0)
+
+}  // namespace xllm::kernel::ilu