7 citations · 21 across the 12 of their papers we have counts for
5 papers · 1 filter
Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs
Tianheng Ling, Chao Qian, Gregor Schiele
This study addresses the deployment challenges of integer-only quantized Transformers on resource-constrained embedded FPGAs (Xilinx Spartan-7 XC7S15). We enhanced the flexibility…
An Automated Approach to Collecting and Labeling Time Series Data for Event Detection Using Elastic Node Hardware
Tianheng Ling, Islam Mansour, Chao Qian +1
Recent advancements in IoT technologies have underscored the importance of using sensor data to understand environmental contexts effectively. This paper introduces a novel embedde…
Idle is the New Sleep: Configuration-Aware Alternative to Powering Off FPGA-Based DL Accelerators During Inactivity
Chao Qian, Christopher Cichiwskyj, Tianheng Ling +1
In the rapidly evolving Internet of Things (IoT) domain, we concentrate on enhancing energy efficiency in Deep Learning accelerators on FPGA-based heterogeneous platforms, aligning…
Integer-only Quantized Transformers for Embedded FPGA-based Time-series Forecasting in AIoT
Tianheng Ling, Chao Qian, Gregor Schiele
This paper presents the design of a hardware accelerator for Transformers, optimized for on-device time-series forecasting in AIoT systems. It integrates integer-only quantization…
Towards Auto-Building of Embedded FPGA-based Soft Sensors for Wastewater Flow Estimation
Tianheng Ling, Chao Qian, Gregor Schiele
Executing flow estimation using Deep Learning (DL)-based soft sensors on resource-limited IoT devices has demonstrated promise in terms of reliability and energy efficiency. Howeve…