26 citations · 64 across the 21 of their papers we have counts for
10 papers · 1 filter
Scope: A Scalable Merged Pipeline Framework for Multi-Chip-Module NN Accelerators
Zongle Huang, Hongyang Jia, Kaiwei Zou +1
Neural network (NN) accelerators with multi-chip-module (MCM) architectures enable integration of massive computation capability; however, they face challenges of computing resourc…
Hecaton: Training Large Language Models with Scalable Chiplet Systems
Zongle Huang, Shupei Fan, Chen Tang +3
Large Language Models (LLMs) have achieved remarkable success in various fields, but their training and finetuning require massive computation and memory, necessitating parallelism…
ASMCap: An Approximate String Matching Accelerator for Genome Sequence Analysis Based on Capacitive Content Addressable Memory
Hongtao Zhong, Zhonghao Chen, Wenqin Huangfu +8
Genome sequence analysis is a powerful tool in medical and scientific research. Considering the inevitable sequencing errors and genetic variations, approximate string matching (AS…
A 65nm 8b-Activation 8b-Weight SRAM-Based Charge-Domain Computing-in-Memory Macro Using A Fully-Parallel Analog Adder Network and A Single-ADC Interface
Guodong Yin, Mufeng Zhou, Yiming Chen +9
Performing data-intensive tasks in the von Neumann architecture is challenging to achieve both high performance and power efficiency due to the memory wall bottleneck. Computing-in…
GRAPHIC: GatheR-And-Process in Highly parallel with In-SSD Compression Architecture in Very Large-Scale Graph
Yiming Chen, Guohao Dai, Mufeng Zhou +8
Graph convolutional network (GCN), an emerging algorithm for graph computing, has achieved promising performance in graphstructure tasks. To achieve acceleration for data-intensive…
ALL-MASK: A Reconfigurable Logic Locking Method for Multicore Architecture with Sequential-Instruction-Oriented Key
Jianfeng Wang, Zhonghao Chen, Jiahao Zhang +9
Intellectual property (IP) piracy has become a non-negligible problem as the integrated circuit (IC) production supply chain is becoming increasingly globalized and separated that…
YOLoC: DeploY Large-Scale Neural Network by ROM-based Computing-in-Memory using ResiduaL Branch on a Chip
Yiming Chen, Guodong Yin, Zhanhong Tan +6
Computing-in-memory (CiM) is a promising technique to achieve high energy efficiency in data-intensive matrix-vector multiplication (MVM) by relieving the memory bottleneck. Unfort…
FAST: A Fully-Concurrent Access Technique to All SRAM Rows for Enhanced Speed and Energy Efficiency in Data-Intensive Applications
Yiming Chen, Yushen Fu, Mingyen Lee +5
Compute-in-memory (CiM) is a promising approach to improving the computing speed and energy efficiency in dataintensive applications. Beyond existing CiM techniques of bitwise logi…
High Area/Energy Efficiency RRAM CNN Accelerator with Kernel-Reordering Weight Mapping Scheme Based on Pattern Pruning
Songming Yu, Yongpan Liu, Lu Zhang +5
Resistive Random Access Memory (RRAM) is an emerging device for processing-in-memory (PIM) architecture to accelerate convolutional neural network (CNN). However, due to the highly…
Low Overhead Online Data Flow Tracking for Intermittently Powered Non-volatile FPGAs
Xinyi Zhang, Clay Patterson, Yongpan Liu +3
Energy harvesting is an attractive way to power future IoT devices since it can eliminate the need for battery or power cables. However, harvested energy is intrinsically unstable.…