feat: CCCL CachingDeviceAllocator LD_PRELOAD — bypass CoreX expandable_segments ASSERT

从 CCCL upstream cub/cub/util_allocator.cuh 提取 CachingDeviceAllocator
核心算法，去掉所有 CUB/CCCL 宏依赖，编译为独立 .so。

用 LD_PRELOAD 拦截 cudaMalloc/cudaFree，路由到 CUB 的 geometric-bin
缓存分配器。同时在 constructor 中 strip PYTORCH_CUDA_ALLOC_CONF 里的
expandable_segments 配置，避免 CoreX CUDACachingAllocator.cpp:545 ASSERT。

BI-V100 调优参数:
  bin_growth=8, min_bin=3 (512B), max_bin=13 (~550MB)
  max_cached_bytes=4GB per device (32GB卡的合理上限)

真机测试步骤:
  1. bash build_cccl_preload.sh
  2. LD_PRELOAD=./libcccl_allocator.so CCCL_ALLOC_DEBUG=1 \
     PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
     python3 verify_preload.py

qwen3_6_scripts/cccl_preload/build_cccl_preload.sh

@@ -0,0 +1,112 @@
+#!/usr/bin/env bash
+# Build libcccl_allocator.so — LD_PRELOAD .so for CUB CachingDeviceAllocator
+#
+# Usage:
+#   bash build_cccl_preload.sh [output_dir]
+#
+# On BI-V100 with CoreX SDK:
+#   bash build_cccl_preload.sh /workspace/qwen3_6_scripts/cccl_preload
+#
+# The .so intercepts cudaMalloc/cudaFree and routes through CUB's
+# caching allocator, bypassing CoreX's "expandable segment not supported"
+# ASSERT in CUDACachingAllocator.cpp:545.
+
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+OUTPUT_DIR="${1:-${SCRIPT_DIR}}"
+SRC="${SCRIPT_DIR}/cccl_allocator_preload.cu"
+OUT="${OUTPUT_DIR}/libcccl_allocator.so"
+
+# Find CoreX clang++ (preferred) or system g++
+if [[ -x /usr/local/corex-3.2.3/bin/clang++ ]]; then
+    CXX=/usr/local/corex-3.2.3/bin/clang++
+    echo "[build] Using CoreX clang++: ${CXX}"
+elif [[ -x /usr/local/corex/bin/clang++ ]]; then
+    CXX=/usr/local/corex/bin/clang++
+    echo "[build] Using CoreX clang++ (alt): ${CXX}"
+else
+    CXX=g++
+    echo "[build] CoreX clang++ not found, falling back to g++"
+fi
+
+# Find CUDA include path
+CUDA_INC=""
+for candidate in \
+    /usr/local/corex/include \
+    /usr/local/cuda/include \
+    /usr/local/corex/lib64/clang/16/include \
+    ; do
+    if [[ -f "${candidate}/cuda_runtime_api.h" ]]; then
+        CUDA_INC="${candidate}"
+        break
+    fi
+done
+
+# Find CUDA lib path for linking
+CUDA_LIB=""
+for candidate in \
+    /usr/local/corex/lib64 \
+    /usr/local/cuda/lib64 \
+    ; do
+    if [[ -f "${candidate}/libcudart.so" ]]; then
+        CUDA_LIB="${candidate}"
+        break
+    fi
+done
+
+if [[ -z "${CUDA_INC}" ]]; then
+    echo "[WARN] cuda_runtime_api.h not found — trying compile anyway"
+fi
+
+echo "[build] CUDA include: ${CUDA_INC:-system}"
+echo "[build] CUDA lib: ${CUDA_LIB:-system}"
+echo "[build] Source: ${SRC}"
+echo "[build] Output: ${OUT}"
+
+# Build as shared library
+# -x cuda or -x c++ depending on compiler
+if [[ "${CXX}" == *clang++* ]]; then
+    # CoreX clang++ can compile .cu natively
+    ${CXX} \
+        -shared -fPIC \
+        -O2 \
+        ${CUDA_INC:+-I"${CUDA_INC}"} \
+        ${CUDA_LIB:+-L"${CUDA_LIB}"} \
+        -lcudart \
+        -ldl \
+        -std=c++17 \
+        -o "${OUT}" \
+        "${SRC}"
+else
+    # g++ needs .cu renamed or treated as C++
+    # cuda_runtime_api.h should still work with host compiler
+    ${CXX} \
+        -shared -fPIC \
+        -O2 \
+        ${CUDA_INC:+-I"${CUDA_INC}"} \
+        ${CUDA_LIB:+-L"${CUDA_LIB}"} \
+        -lcudart \
+        -ldl \
+        -std=c++17 \
+        -x c++ \
+        -o "${OUT}" \
+        "${SRC}"
+fi
+
+if [[ -f "${OUT}" ]]; then
+    SIZE=$(stat -c%s "${OUT}" 2>/dev/null || stat -f%z "${OUT}" 2>/dev/null || echo "?")
+    echo "[build] SUCCESS: ${OUT} (${SIZE} bytes)"
+    echo ""
+    echo "Usage:"
+    echo "  LD_PRELOAD=${OUT} CCCL_ALLOC_DEBUG=1 python3 -c 'import torch; t=torch.zeros(1024, device=\"cuda\")'"
+    echo ""
+    echo "In computility-run.yaml, add to env:"
+    echo "  - name: LD_PRELOAD"
+    echo "    value: /workspace/qwen3_6_scripts/cccl_preload/libcccl_allocator.so"
+    echo "  - name: PYTORCH_CUDA_ALLOC_CONF"
+    echo "    value: expandable_segments:True"
+else
+    echo "[build] FAILED"
+    exit 1
+fi