@inproceedings{80645eda6ec14390ae97d5a5254d9c03,
title = "Graviton: A Reconfigurable Memory-Compute Fabric for Data Intensive Applications",
abstract = "The rigid organization and distribution of computational and memory resources often limits how well accelerators can cope with changing algorithms and increasing dataset sizes and limits how efficiently they use their computational and memory resources. In this work, we leverage a novel computing paradigm and propose a new memory-based reconfigurable fabric, Graviton. We demonstrate the ability to dynamically trade memory for compute and vice versa, and can tune the architecture of the underlying hardware to suit the memory and compute requirements of the application. On a die-to-die basis, Graviton provides up to 47X more on-chip memory capacity over an Alveo U250 SLR, with just an additional 1.7 \% area on a die-to-die basis than modern FPGAs, and is 28.7X faster, on average, on a range of compute and data intensive tasks.",
keywords = "Logic folding, Reconfigurable architectures",
author = "Ashutosh Dhar and Paul Reckamp and Jinjun Xiong and Hwu, \{Wen mei\} and Deming Chen",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 17th International Symposium on Applied Reconfigurable Computing, ARC 2021 ; Conference date: 29-06-2021 Through 30-06-2021",
year = "2021",
doi = "10.1007/978-3-030-79025-7\_18",
language = "English",
isbn = "9783030790240",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "254--264",
editor = "Steven Derrien and Frank Hannig and Diniz, \{Pedro C.\} and Daniel Chillet",
booktitle = "Applied Reconfigurable Computing. Architectures, Tools, and Applications - 17th International Symposium, ARC 2021, Proceedings",
address = "Germany",
}