TileLoom compiles tile-based languages to spatial dataflow hardware by distributing tiles across cores and optimizing data reuse via on-chip networks, delivering vendor-comparable performance on Tenstorrent systems.
Maestro: A data-centric approach to under- stand reuse, performance, and hardware cost of dnn map- pings.IEEE micro, 40(3):20–29, 2020
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TileLoom: Automatic Dataflow Planning for Tile-Based Languages on Spatial Dataflow Accelerators
TileLoom compiles tile-based languages to spatial dataflow hardware by distributing tiles across cores and optimizing data reuse via on-chip networks, delivering vendor-comparable performance on Tenstorrent systems.