2 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
CoMeFa: Compute-in-Memory Blocks for FPGAs
Aman Arora, Tanmay Anand, Aatman Borda +4
Block RAMs (BRAMs) are the storage houses of FPGAs, providing extensive on-chip memory bandwidth to the compute units implemented using Logic Blocks (LBs) and Digital Signal Proces…
Weightless Neural Networks for Efficient Edge Inference
Zachary Susskind, Aman Arora, Igor Dantas Dos Santos Miranda +8
Weightless Neural Networks (WNNs) are a class of machine learning model which use table lookups to perform inference. This is in contrast with Deep Neural Networks (DNNs), which us…
Compute RAMs: Adaptable Compute and Storage Blocks for DL-Optimized FPGAs
Aman Arora, Bagus Hanindhito, Lizy K. John
The configurable building blocks of current FPGAs -- Logic blocks (LBs), Digital Signal Processing (DSP) slices, and Block RAMs (BRAMs) -- make them efficient hardware accelerators…
Koios: A Deep Learning Benchmark Suite for FPGA Architecture and CAD Research
Aman Arora, Andrew Boutros, Daniel Rauch +9
With the prevalence of deep learning (DL) in many applications, researchers are investigating different ways of optimizing FPGA architecture and CAD to achieve better quality-of-re…
Virtual-Link: A Scalable Multi-Producer, Multi-Consumer Message Queue Architecture for Cross-Core Communication
Qinzhe Wu, Jonathan Beard, Ashen Ekanayake +2
Cross-core communication is increasingly a bottleneck as the number of processing elements increase per system-on-chip. Typical hardware solutions to cross-core communication are o…