most citedPushing up to the Limit of Memory Bandwidth and Capacity Utilization for Efficient LLM Decoding on Embedded FPGA

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cs.AR2025★ 1 cited

Pushing up to the Limit of Memory Bandwidth and Capacity Utilization for Efficient LLM Decoding on Embedded FPGA

Jindong Li, Tenglong Li, Guobin Shen +3

The extremely high computational and storage demands of large language models have excluded most edge devices, which were widely used for efficient machine learning, from being via…

cs.NE2025

: Enhanced Information Flow in Spiking Neural Networks with High Hardware Compatibility

Guobin Shen, Jindong Li, Tenglong Li +2

Spiking Neural Networks (SNNs) hold promise for energy-efficient, biologically inspired computing. We identify substantial informatio loss during spike transmission, linked to temp…

cs.AR2024

Revealing Untapped DSP Optimization Potentials for FPGA-Based Systolic Matrix Engines

Jindong Li, Tenglong Li, Guobin Shen +3

Systolic architectures are widely embraced by neural network accelerators for their superior performance in highly parallelized computation. The DSP48E2s serve as dedicated arithme…