12 citations · 20 across the 6 of their papers we have counts for
4 papers · 1 filter
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs
Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao +4
Precise hardware performance models play a crucial role in code optimizations. They can assist compilers in making heuristic decisions or aid autotuners in identifying the optimal…
FLuRKA: Fast and accurate unified Low-Rank & Kernel Attention
Ahan Gupta, Hao Guo, Yueming Yuan +2
Many efficient self-attention techniques have become prevalent since the inception of the transformer architecture. Two popular classes of these techniques a…
SENSEi: Input-Sensitive Compilation for Accelerating GNNs
Damitha Lenadora, Vimarsh Sathia, Gerasimos Gerogiannis +3
Over the years, many frameworks and optimization techniques have been proposed to accelerate graph neural networks (GNNs). Compared to the optimizations explored in these systems,…
Learning Large Graph Property Prediction via Graph Segment Training
Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija +5
Learning to predict properties of large graphs is challenging because each prediction requires the knowledge of an entire graph, while the amount of memory available during trainin…