3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.DC2025
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…
cs.AR2024
PipeOrgan: Efficient Inter-operation Pipelining with Flexible Spatial Organization and Interconnects
Raveesh Garg, Hyoukjun Kwon, Eric Qin +3
Because of the recent trends in Deep Neural Networks (DNN) models being memory-bound, inter-operator pipelining for DNN accelerators is emerging as a promising optimization. Inter-…
cs.AR2022★ 3 cited
Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity
Eric Qin, Raveesh Garg, Abhimanyu Bambhaniya +5
Recently, numerous sparse hardware accelerators for Deep Neural Networks (DNNs), Graph Neural Networks (GNNs), and scientific computing applications have been proposed. A common ch…