3 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
HARP: A Taxonomy for Heterogeneous and Hierarchical Processors for Mixed-reuse Workloads
Raveesh Garg, Michael Pellauer, Tushar Krishna
Artificial intelligence (AI) application domains consist of a mix of tensor operations with high and low arithmetic intensities (aka reuse). Hierarchical (i.e. compute along multip…
CELLO: Co-designing Schedule and Hybrid Implicit/Explicit Buffer for Complex Tensor Reuse
Raveesh Garg, Michael Pellauer, Sivasankaran Rajamanickam +1
Tensor algebra accelerators have been gaining popularity for running high-performance computing (HPC) workloads. Identifying optimal schedules for individual tensor operations and…
Understanding the Design-Space of Sparse/Dense Multiphase GNN dataflows on Spatial Accelerators
Raveesh Garg, Eric Qin, Francisco Muñoz-Martínez +8
Graph Neural Networks (GNNs) have garnered a lot of recent interest because of their success in learning representations from graph-structured data across several critical applicat…