CoMeFa: Compute-in-Memory Blocks for FPGAs-Reference-Cited by-同舟云学术

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CoMeFa: Compute-in-Memory Blocks for FPGAs

Published:2022-05-15 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 30th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)
language:
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Author:

Arora Aman¹,Anand Tanmay¹,Borda Aatman¹,Sehgal Rishabh¹,Hanindhito Bagus¹,Kulkarni Jaydeep¹,John Lizy K.¹

Affiliation:

1. The University of Texas at Austin

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9786061/9786064/09786179.pdf?arnumber=9786179

Reference38 articles.

1. Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks;sun;Advances in neural information processing systems,2019

2. Hybrid Memory Cube Controller IP Core User Guide v16.0,2016

3. Intel Arria 10 Transceiver PHY User Guide,2021

4. Intel Arria 10 Product Table,2021

5. Scaling equations for the accurate prediction of CMOS device performance from 180 nm to 7 nm

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1. PIMSAB: A P rocessing- I n- M emory System with S patially- A ware Communication and B it-Serial-Aware Computation;ACM Transactions on Architecture and Code Optimization;2024-09-05

2. Towards High-Throughput Neural Network Inference with Computational BRAM on Nonvolatile FPGAs;2024 Design, Automation & Test in Europe Conference & Exhibition (DATE);2024-03-25

3. An All-digital Compute-in-memory FPGA Architecture for Deep Learning Acceleration;ACM Transactions on Reconfigurable Technology and Systems;2024-02-12

4. M4BRAM: Mixed-Precision Matrix-Matrix Multiplication in FPGA Block RAMs;2023 International Conference on Field Programmable Technology (ICFPT);2023-12-12

5. Koios 2.0: Open-Source Deep Learning Benchmarks for FPGA Architecture and CAD Research;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-11

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