Lazy loading is not enabled in the CUDA stack by default in this release. This is lower overall than the total latency without lazy loading.Īll libraries used with lazy loading must be built with 11.7+ to be eligible for lazy loading. The tradeoff is a minimal amount of latency at the point in the application where the functions are first loaded. What this means is that functions and libraries load faster on the CPU, with sometimes substantial memory footprint reductions. Lazy module loadingīuilding on the lazy kernel loading feature in 11.7, NVIDIA added lazy loading to the CPU module side. NVIDIA Hopper and NVIDIA Ada architecture supportĬUDA applications can immediately benefit from increased streaming multiprocessor (SM) counts, higher memory bandwidth, and higher clock rates in new GPU families.ĬUDA and CUDA libraries expose new performance optimizations based on GPU hardware architecture enhancements. This post offers an overview of the key capabilities. The full programming model enhancements for the NVIDIA Hopper architecture will be released starting with the CUDA Toolkit 12 family.ĬUDA 11.8 has several important features. New architecture-specific features in NVIDIA Hopper and Ada Lovelace are initially being exposed through libraries and framework enhancements. This release is focused on enhancing the programming model and CUDA application speedup through new hardware capabilities. NVIDIA announces the newest CUDA Toolkit software release, 11.8.
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