Reduce CUDA Binary Bloat via Kernel Consolidation
Explores techniques for reducing CUDA binary size by consolidating multiple similar kernels into parameterized versions, decreasing compilation time and
CUDA developers reduce binary bloat by consolidating kernel instantiations across shared objects.
Single-Translation-Unit Pattern:
Enforce one compilation unit per kernel to prevent duplicate instantiations. Move kernel definitions into a single .cu file and expose through headers with forward declarations only.
Runtime Parameterization:
Convert compile-time template arguments to runtime parameters where performance impact is negligible. Replace template<int N> __global__ void kernel() with __global__ void kernel(int n) for non-critical paths.
Build System Checks:
Add CI validation to detect binary size regressions. Use readelf -s libname.so | grep FUNC to audit exported symbols and identify duplicates.
Reference Implementation: The cuML project documented this approach in their PyPI distribution work, using these techniques to maintain performance while cutting build times and staying within platform limits.
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