16 citations · 69 across the 23 of their papers we have counts for
3 papers · 1 filter
SCALE-Sim: Systolic CNN Accelerator Simulator
Ananda Samajdar, Yuhao Zhu, Paul Whatmough +2
Systolic Arrays are one of the most popular compute substrates within Deep Learning accelerators today, as they provide extremely high efficiency for running dense matrix multiplic…
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware
Ananda Samajdar, Parth Mannan, Kartikay Garg +1
Modern deep learning systems rely on (a) a hand-tuned neural network topology, (b) massive amounts of labeled training data, and (c) extensive training over large-scale compute res…
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach Using MAESTRO
Hyoukjun Kwon, Prasanth Chatarasi, Michael Pellauer +3
The data partitioning and scheduling strategies used by DNN accelerators to leverage reuse and perform staging are known as dataflow, and they directly impact the performance and e…