#machine learning
Dec 2025
SparsePixels: Efficient Convolution for Sparse Data on FPGAs
This work introduces SparsePixels, a framework that implements sparse convolution on FPGAs by selectively retaining and computing on a small subset of active input pixels while ignoring the rest, which aims to benefit future algorithm development for efficient data readout in modern experiments with strict latency requirements of microseconds or below.
Ho Fung Tsoi, D. Rankin, Vladimir Loncar et al.
· arXiv.org · 0 citations