Tianheng Ling

According to our database, Tianheng Ling authored at least 14 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Exploring energy efficiency of LSTM accelerators: A parameterized architecture design for embedded FPGAs.

Chao Qian, Tianheng Ling, Gregor Schiele

J. Syst. Archit., 2024

Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs.

Tianheng Ling, Chao Qian, Gregor Schiele

CoRR, 2024

Data-driven Modeling of Combined Sewer Systems for Urban Sustainability: An Empirical Evaluation.

Vipin Singh, Tianheng Ling, Teodor Chiaburu, Felix Biessmann

CoRR, 2024

An Automated Approach to Collecting and Labeling Time Series Data for Event Detection Using Elastic Node Hardware.

Tianheng Ling, Islam Mansour, Chao Qian, Gregor Schiele

CoRR, 2024

Integer-only Quantized Transformers for Embedded FPGA-based Time-series Forecasting in AIoT.

Tianheng Ling, Chao Qian, Gregor Schiele

CoRR, 2024

Towards Auto-Building of Embedded FPGA-based Soft Sensors for Wastewater Flow Estimation.

Tianheng Ling, Chao Qian, Gregor Schiele

CoRR, 2024

FlowPrecision: Advancing FPGA-Based Real-Time Fluid Flow Estimation with Linear Quantization.

Tianheng Ling, Julian Hoever, Chao Qian, Gregor Schiele

Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2024

Idle is the New Sleep: Configuration-Aware Alternative to Powering Off FPGA-Based DL Accelerators During Inactivity.

Chao Qian, Christopher Cichiwskyj, Tianheng Ling, Gregor Schiele

Proceedings of the Architecture of Computing Systems - 37th International Conference, 2024

2023

On-Device Soft Sensors: Real-Time Fluid Flow Estimation from Level Sensor Data.

Tianheng Ling, Chao Qian, Gregor Schiele

CoRR, 2023

A Study of Quantisation-aware Training on Time Series Transformer Models for Resource-constrained FPGAs.

Tianheng Ling, Chao Qian, Lukas Einhaus, Gregor Schiele

CoRR, 2023

ElasticAI: Creating and Deploying Energy-Efficient Deep Learning Accelerator for Pervasive Computing.

Chao Qian, Tianheng Ling, Gregor Schiele

Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

On-Device AI: Quantization-Aware Training of Transformers in Time-Series.

Tianheng Ling, Gregor Schiele

Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

Energy Efficient LSTM Accelerators for Embedded FPGAs Through Parameterised Architecture Design.

Chao Qian, Tianheng Ling, Gregor Schiele

Proceedings of the Architecture of Computing Systems - 36th International Conference, 2023

2022

Enhancing Energy-Efficiency by Solving the Throughput Bottleneck of LSTM Cells for Embedded FPGAs.

Chao Qian, Tianheng Ling, Gregor Schiele

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022