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Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Announce Type: replace Abstract: NVIDIA's CUDA Tile (CuTile) introduces a Python-based, tile-centric abstraction for GPU kernel development that aims to simplify programming while retaining Tensor Core and Tensor Memory Accelerator (TMA) efficiency on modern GPUs. We present the first independent, cross-architecture evaluation of CuTile against established approaches such as cuBLAS, Triton, WMMA, and raw SIMT on three NVIDIA GPUs spanning Hopper and Blackwell: H100 NVL, B200, and RTX PRO...

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Nvidia Cosmos 3

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GPU Acceleration of Learning With Errors KEMs Using OpenACC for Post-Quantum Cryptography

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