168 citations · 743 across the 44 of their papers we have counts for
44 papers
CHARM: Composing Heterogeneous Accelerators for Matrix Multiply on Versal ACAP Architecture
Jinming Zhuang, Jason Lau, Hanchen Ye +10
Dense matrix multiply (MM) serves as one of the most heavily used kernels in deep learning applications. To cope with the high computation demands of these applications, heterogene…
HiKonv: Maximizing the Throughput of Quantized Convolution With Novel Bit-wise Management and Computation
Yao Chen, Junhao Pan, Xinheng Liu +2
Quantization for CNN has shown significant progress with the intention of reducing the cost of computation and storage with low-bitwidth data representations. There are, however, n…
ORB-based SLAM accelerator on SoC FPGA
Vibhakar Vemulapati, Deming Chen
Simultaneous Localization and Mapping (SLAM) is one of the main components of autonomous navigation systems. With the increase in popularity of drones, autonomous navigation on low…
Chimera: A Hybrid Machine Learning Driven Multi-Objective Design Space Exploration Tool for FPGA High-Level Synthesis
Mang Yu, Sitao Huang, Deming Chen
In recent years, hardware accelerators based on field-programmable gate arrays (FPGAs) have been widely adopted, thanks to FPGAs' extraordinary flexibility. However, with the high…
Compilation and Optimizations for Efficient Machine Learning on Embedded Systems
Xiaofan Zhang, Yao Chen, Cong Hao +3
Deep Neural Networks (DNNs) have achieved great success in a variety of machine learning (ML) applications, delivering high-quality inferencing solutions in computer vision, natura…
AutoDistill: an End-to-End Framework to Explore and Distill Hardware-Efficient Language Models
Xiaofan Zhang, Zongwei Zhou, Deming Chen +1
Recently, large pre-trained models have significantly improved the performance of various Natural LanguageProcessing (NLP) tasks but they are expensive to serve due to long serving…