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Open access Sep 2026

When and Why to Use TMA: A Workload-Grounded Characterization of Tensor Memory Acceleration on NVIDIA Hopper GPUs

The Tensor Memory Accelerator (TMA), introduced on NVIDIA Hopper, is used pervasively in production GPU kernels yet its usage is conspicuously selective: expert kernel developers in CUTLASS, FlashAttention-3, and FlashInfer apply TMA to some tensor operands within a kernel but fall back to cp.async, direct global loads...

Christin Bose, Cesar Avalos Baddouh, Jun-Rui Pan et al. · 0 citations
Preprint Aug 2026

Architecting the Next Generation of Asynchronous, Distributed GPUs for the AI Era

This work presents a cycle-level simulation framework designed to accurately model modern GPU generations, including Ampere, Hopper, and Blackwell, and conducts architectural case studies to evaluate emerging design trajectories, including chiplet topology scaling, expanded SRAM capacity and bandwidth, and inter-GPU pr...

Junrui Pan, Wei-Li An, Cesar Avalos Baddouh et al. · 2 citations · ⚡2

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