10 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.AR2021
Capstan: A Vector RDA for Sparsity
Alexander Rucker, Matthew Vilim, Tian Zhao +3
This paper proposes Capstan: a scalable, parallel-patterns-based, reconfigurable dataflow accelerator (RDA) for sparse and dense tensor applications. Instead of designing for one a…
cs.DC2019★ 10 cited
Serving Recurrent Neural Networks Efficiently with a Spatial Accelerator
Tian Zhao, Yaqi Zhang, Kunle Olukotun
Recurrent Neural Network (RNN) applications form a major class of AI-powered, low-latency data center workloads. Most execution models for RNN acceleration break computation graphs…
cs.DB2019
Efficient Multiway Hash Join on Reconfigurable Hardware
Kunle Olukotun, Raghu Prabhakar, Rekha Singhal +2
We propose the algorithms for performing multiway joins using a new type of coarse grain reconfigurable hardware accelerator~-- ``Plasticine''~-- that, compared with other accelera…