activity
20232026
most citedField-Programmable Gate Array Architecture for Deep Learning: Survey & Future Directions

17 citations · 18 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AR2026

NIFA: Nonlinear IMC enhanced FPGA for efficient ML inference

Jiajun Hu, Ruthwik Reddy Sunketa, Lei Zhao +3

Recent FPGAs have improved deep learning (DL) inference efficiency through dedicated tensor blocks and in-BRAM computation. ReRAM-based analog in-memory computing (IMC) pushes effi…

cs.AR2026

Boosting FPGA Performance with Direct BRAM-DSP Paths

Jiajun Hu, Ruthwik Reddy Sunketa, Andrew Boutros +1

Efficient data movement between memory and compute units is a key performance bottleneck in modern FPGA designs, particularly for deep learning (DL) workloads. In typical FPGA arch…

quant-ph2025

LUNA: LUT-Based Neural Architecture for Fast and Low-Cost Qubit Readout

M. A. Farooq, G. Di Guglielmo, A. Rajagopala +3

Qubit readout is a critical operation in quantum computing systems, which maps the analog response of qubits into discrete classical states. Deep neural networks (DNNs) have recent…

cs.AR2025

CarbonSet: A Dataset to Analyze Trends and Benchmark the Sustainability of CPUs and GPUs

Jiajun Hu, Chetan Choppali Sudarshan, Vidya A. Chhabria +1

Over the years, the chip industry has consistently developed high-performance processors to address the increasing demands across diverse applications. However, the rapid expansion…

cs.DC2025

SAF: Scalable Acceleration Framework for dynamic and flexible scaling of FPGAs

Masudul Hassan Quraishi, Michael Riera, Fengbo Ren +2

FPGAs are increasingly gaining traction in cloud and edge computing environments due to their hardware flexibility, low latency, and low energy consumption. However, the existing h…

cs.AR2024★ 17 cited

Field-Programmable Gate Array Architecture for Deep Learning: Survey & Future Directions

Andrew Boutros, Aman Arora, Vaughn Betz

Deep learning (DL) is becoming the cornerstone of numerous applications both in datacenters and at the edge. Specialized hardware is often necessary to meet the performance require…

cs.AR2023★ 1 cited

GreenFPGA: Evaluating FPGAs as Environmentally Sustainable Computing Solutions

Chetan Choppali Sudarshan, Aman Arora, Vidya A. Chhabria

Growing global concerns about climate change highlight the need for environmentally sustainable computing. The ecological impact of computing, including operational and embodied, i…