Rubick: A Synthesis Framework for Spatial Architectures via Dataflow Decomposition-Reference-Cited by-同舟云学术

Rubick: A Synthesis Framework for Spatial Architectures via Dataflow Decomposition

Published:2023-07-09 Issue: Volume: Page:
ISSN:
Container-title:2023 60th ACM/IEEE Design Automation Conference (DAC)
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Author:

Luo Zizhang¹,Lu Liqiang²,Zheng Size³,Yin Jieming⁴,Cong Jason⁵,Yin Jianwei²,Liang Yun¹

Affiliation:

1. Peking University,School of Integrated Circuits

2. Zhejiang University,College of Computer Science and Technology

3. School of Computer Science,Peking University

4. Nanjing University of Posts and Telecommunications,School of Computer Science

5. University of California,Computer Science Department,Los Angeles

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10247654/10247655/10247743.pdf?arnumber=10247743

Reference25 articles.

1. Tensor Decompositions and Applications

2. EMS

3. MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings

4. Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow

5. Automatic generation of spatial accelerator for tensor algebra;jia;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems(TCAD),2022

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4. Khronos: Fusing Memory Access for Improved Hardware RTL Simulation;56th Annual IEEE/ACM International Symposium on Microarchitecture;2023-10-28

5. Rubick: A Unified Infrastructure for Analyzing, Exploring, and Implementing Spatial Architectures via Dataflow Decomposition;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023