4 papers
SNN: Sub-bit Spiking Neural Networks
Wenjie Wei, Malu Zhang, Jieyuan Zhang +8
Spiking Neural Networks (SNNs) offer an energy-efficient paradigm for machine intelligence, but their continued scaling poses challenges for resource-limited deployment. Despite re…
What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips
Renjie Li, Wenjie Wei, Qi Xin +7
Large language models (LLMs) are rapidly pushing the limits of contemporary computing hardware. For example, training GPT-3 has been estimated to consume around 1300 MWh of electri…
Q-SNNs: Quantized Spiking Neural Networks
Wenjie Wei, Yu Liang, Ammar Belatreche +6
Brain-inspired Spiking Neural Networks (SNNs) leverage sparse spikes to represent information and process them in an asynchronous event-driven manner, offering an energy-efficient…
Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate
Pengfei Sun, Jibin Wu, Malu Zhang +2
Recurrent Neural Networks (RNNs) are widely recognized for their proficiency in modeling temporal dependencies, making them highly prevalent in sequential data processing applicati…