NVIDIA publishes guide to accelerating Mamba-2 forward pass with CUDA Tile kernels
Overview
NVIDIA publishes a technical blog post describing how to write high-performance Mamba-2 forward pass kernels using CUDA Tile (cuTile).
The post says cuTile is a Python-based domain-specific language and parallel programming model for NVIDIA GPUs that abstracts thread- and warp-level scheduling behind tile-centric primitives, letting developers write GPU kernels in Python while compiler optimizations handle performance tuning.
The only source so far is NVIDIA's own Technical Blog. The report does not include benchmark results or performance figures for the Mamba-2 kernels.
Written by AI from the articles below · updated Oct 19, 1:32 PM ET
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- NVIDIA Technical BlogOfficialNVIDIA's CUDA Tile lets developers write GPU kernels in Python for Mamba-2 acceleration
AINVIDIA describes CUDA Tile (cuTile), a Python-based DSL and parallel programming model for NVIDIA GPUs. It abstracts thread- and warp-level scheduling behind tile-centric primitives, so developers can write GPU kernels in Python while compiler optimizations handle performance tuning.
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