Automating GPU Kernel Translation with AI Agents: cuTile Python to cuTile.jl
Mirrored from NVIDIA Developer Blog for archival readability. Support the source by reading on the original site.
NVIDIA CUDA Tile (cuTile) is a tile-based programming model that enables developers to write GPU kernels in terms of tile-level operations—loads, stores, and...NVIDIA CUDA Tile (cuTile) is a tile-based programming model that enables developers to write GPU kernels in terms of tile-level operations—loads, stores, and matrix multiply-accumulate—rather than manually coordinating threads, warps, and shared memory. cuTile.jl brings the same tile-based approach to the dynamic programming language Julia. Users can write custom GPU kernels without dropping…
More from NVIDIA Developer Blog
-
Serve Qwen3.8-2.4T-A95B, a 2.4T-Parameter Model, with Configurable Reasoning on NVIDIA GB300 NVL72
Aug 12
-
How to Choose Full-Stack Observability for NVIDIA AI Factories
Aug 12
-
NVIDIA JetPack 7.2.1 Adds Agentic Video Skills and T3000 Emulation
Aug 11
-
NVIDIA Nemotron 3.5 Lightning Delivers Fast, Accurate Specialized Task Execution for Long-Running Agents
Aug 11
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.