Guest Editorial: Communication-Aware Designs and Methodologies for Reliable and Adaptable On-Chip AI SubSystems and Accelerators

Kun-Chih Chen; Masoumeh Ebrahimi; Maurizio Palesi; Tim Kogel

An Overview of Efficient Interconnection Networks for Deep Neural Network Accelerators

Seyed Morteza Nabavinejad; Mohammad Baharloo; Kun-Chih Chen; Maurizio Palesi; Tim Kogel; Masoumeh Ebrahimi

A Communication-Aware DNN Accelerator on ImageNet Using In-Memory Entry-Counting Based Algorithm-Circuit-Architecture Co-Design in 65-nm CMOS

Haozhe Zhu; Chixiao Chen; Shiwei Liu; Qiaosha Zou; Mingyu Wang; Lihua Zhang; Xiaoyang Zeng; C.-J. Richard Shi

CASH-RAM: Enabling In-Memory Computations for Edge Inference Using Charge Accumulation and Sharing in Standard 8T-SRAM Arrays

Amogh Agrawal; Adarsh Kosta; Sangamesh Kodge; Dong Eun Kim; Kaushik Roy

Attention-Based Activation Pruning to Reduce Data Movement in Real-Time AI: A Case-Study on Local Motion Planning in Autonomous Vehicles

Kruttidipta Samal; Marilyn Wolf; Saibal Mukhopadhyay

SRNPU: An Energy-Efficient CNN-Based Super-Resolution Processor With Tile-Based Selective Super-Resolution in Mobile Devices

Juhyoung Lee; Jinsu Lee; Hoi-Jun Yoo

MEM-OPT: A Scheduling and Data Re-Use System to Optimize On-Chip Memory Usage for CNNs On-Board FPGAs

Gianmarco Dinelli; Gabriele Meoni; Emilio Rapuano; Tommaso Pacini; Luca Fanucci

Optimizing Temporal Convolutional Network Inference on FPGA-Based Accelerators

Marco Carreras; Gianfranco Deriu; Luigi Raffo; Luca Benini; Paolo Meloni

A Latency-Optimized Reconfigurable NoC for In-Memory Acceleration of DNNs

Sumit K. Mandal; Gokul Krishnan; Chaitali Chakrabarti; Jae-Sun Seo; Yu Cao; Umit Y. Ogras

Design of a Sparsity-Aware Reconfigurable Deep Learning Accelerator Supporting Various Types of Operations

Shen-Fu Hsiao; Kun-Chih Chen; Chih-Chien Lin; Hsuan-Jui Chang; Bo-Ching Tsai

Hybrid Fixed-Point/Binary Deep Neural Network Design Methodology for Low-Power Object Detection

Jiun-In Guo; Chia-Chi Tsai; Jian-Lin Zeng; Shao-Wei Peng; En-Chih Chang