Route C: replace PyTorch's cudaMalloc/cudaFree with CCCL CUB's
CachingDeviceAllocator via LD_PRELOAD. Eliminates driver-level allocation
overhead by reusing freed GPU memory from a bin-based cache.
Based on cccl_upstream/cub/cub/util_allocator.cuh (901 lines).
Self-contained .so with no CCCL header dependencies at compile time.
Files:
- cccl_preload_allocator.cu: the allocator (405 lines)
- build_cccl_preload_allocator.sh: build script (corex clang++ or g++ fallback)
- test_cccl_preload.sh: smoke test suite for BI-V100
- patch_ops.sh: build during docker build
- computility-run.yaml: LD_PRELOAD env var for runtime
Config via env:
CCCL_ALLOC_BIN_GROWTH=8, MIN_BIN=3, MAX_BIN=13, MAX_CACHED_MB=4096
Test on real machine:
cd qwen3_6_scripts && bash test_cccl_preload.sh
327c2c9044