FCCM 2023 Posters and PhD Forum

Session A — Virtual Posters

Title	Authors
CAKS-NMC: Compiler-Assisted Automatic Kernel Selection for FPGA-based Near-Memory Computing Platforms	V. Iskandar; A. Hantriono; M. Ghany; D. Goehringer
Transformer-OPU: An FPGA-based Overlay Processor for Transformer Networks	Y. Bai; H. Zhou; K. Zhao; J. Chen; J. Yu; K. Wang
FASBM: FPGA-specific Approximate Sum-based Booth multipliers for Energy Efficient Hardware Acceleration of Image Processing and Machine Learning applications	Z. Aizaz; K. Khare; A. Tirmizi
OCMGen: Extended Design Space Exploration with Efficient FPGA Memory Inference	S. Gandham; L. Yin; H. Zheng; M. Lin
An Efficient Piecewise Linear Approximation of Non-linear Operations for Transformer Inference	H. Lu; Q. Mei; K. Wang
SpCNA: An FPGA-based Accelerator for Point Cloud Convolutional Neural Networks	G. Zhou; K. Guo; X. Chen; K. LEUNG
MSBF-LSTM: Most-significant Bit-first LSTM Accelerators with Energy Efficiency Optimisations	S. Bian; H. Li; C. Wang; C. Song; Y. Tang
Moth: A Hardware Accelerator for Neural Radiance Field Inference on FPGA	Y. Wang; Y. Li; H. Zhang; J. Yu; K. Wang

Session B — In-person Posters

Title	Authors
Accelerating FPGA-Based Wi-Fi Transceiver Design and Prototyping by High-Level Synthesis	T. Havinga; X. Jiao; W. Liu; I. Moerman
Runtime Memory Disambiguation for Hybrid-Scheduled High-Level Synthesis	R. Szafarczyk; S. Nabi; W. Vanderbauwhede
Designing a configurable IEEE-compliant FPU that supports variable precision for soft processors	Y. Gao; C. Keilbart; M. Chua; E. Matthews; S. Wilton; L. Shannon
Accelerating 128-bit Floating-Point Matrix Multiplication on FPGAs	F. Kono; N. Nakasato; M. Nakata
ReLoDAQ: Resource-Efficient, Low Overhead 200 Gbit/s Data Acquisition System for 6G Prototyping	C. Karle; M. Neu; J. Pfau; J. Sperling; J. Becker
b8c: SpMV accelerator implementation leveraging high memory bandwidth	J. Oliver; C. Álvarez; T. Cervero; X. Martorell; J. Davis; E. Ayguadé
Making BRAMs Compute: Creating Scalable Computational Memory Fabric Overlays	M. Kabir; J. Hollis; A. Panahi; J. Bakos; M. Huang; D. Andrews
HyBNN: Quantifying and Optimizing Hardware Efficiency of Binary Neural Networks	G. Yang; J. Lei; Z. Fang; Y. Li; J. Zhang; W. Xie
Improving Performance of HPC Kernels on FPGAs Using High-Level Resource Management	A. Filgueras; M. Vidal; D. Jiménez-González; C. Álvarez; X. Martorell
A Flexible and Scalable Reconfigurable FPGA Overlay Architecture for Data-Flow Processing	A. Drewes; V. Burtsev; B. Gurumurthy; M. Wilhelm; D. Broneske; G. Saake; T. Pionteck
Efficient implementation of a Genetic Algorithm for the Capacitated Vehicle Routing Problem on a High-Performance FPGA	M. Heer; J. Quevedo; M. Abdelatti; R. Sendag; M. Sodhi
Decision Forest Training Accelerator Based on Binary Feature Decomposition	T. Van Chu; Y. Mizutani; Y. Nagahara; S. Kumazawa; K. Kawamura; J. Yu; M. Motomura
Accelerating Graph Analytics with oneAPI and Intel FPGAs	J. Bickerstaff; L. Kljucaric; A. George
FEASTS: Feature Extraction Accelerator for Streaming Time Series	P. Yuvaraj; A. Kalantar; E. Keogh; P. Brisk
PRAD: A Bayesian Optimization-based DSE Framework for Parameterized Reconfigurable Architecture Design	B. Peng; S. Sun; Y. Dai
Scalable Quantum Error Correction for Surface Codes using FPGA	N. Liyanage; Y. Wu; A. Deters; L. Zhong
Clustering Classification on FPGAs for Neuromorphic Feature Extraction	L. Kljucaric; D. George
UPTRA: An Ultra-Parameterized Temporal CGRA Modeling and Optimization	Y. Dai; Y. Qiu; Q. Zhu; J. Li; W. Yin; L. Wang

Session C — PhD Forum

Title	Authors
Reformulating the FPGA Routability Prediction Problem with Machine Learning	Andrew David Gunther, Steve Wilton (The Univ. of British Columbia)
Hardware/Software Co-design for Machine Learning Accelerators	Hanqiu Chen, Cong (Callie) Hao (Georgia Institute of Technology)
From Acceleration to Accelerating Acceleration: Modernizing the Accelerator Landscape using High-Level Synthesis	Rishov Sarkar, Cong (Callie) Hao (Georgia Institute of Technology)
Power Side-Channel Attacks and Defenses for Neural Network Accelerators	Vincent Meyers, Mehdi B. Tahoori (Karlsruhe Institute of Technology)
Enabling Elastic Resource Management in Cloud FPGAs via A Multi-layer Collaborative Approach	Wenbin Teng, Xuehai Zhou (University of Science and Technology of China)
A Framework for Graph Machine Learning on Heterogeneous Architecture	Yi-Chien Lin, Viktor Prasanna (University of Southern California, Los Angeles, California)
DataMaster: A GNN-based Data Type Optimizer for Dataflow Design in FPGA	Zheyuan Zou, Xuehai Zhou (University of Science and Technology of China)