4 papers
WorldComp2D: Spatio-semantic Representations of Object Identity and Location from Local Views
SeongMin Jin, Doo Seok Jeong
Learning latent representations that capture both semantic and spatial information is central to efficient spatio-semantic reasoning. However, many existing approaches rely on impl…
Computing-In-Memory Dataflow for Minimal Buffer Traffic
Choongseok Song, Doo Seok Jeong
Computing-In-Memory (CIM) offers a potential solution to the memory wall issue and can achieve high energy efficiency by minimizing data movement, making it a promising architectur…
IterL2Norm: Fast Iterative L2-Normalization
ChangMin Ye, Yonguk Sim, Youngchae Kim +2
Transformer-based large language models are a memory-bound model whose operation is based on a large amount of data that are marginally reused. Thus, the data movement between a ho…
Training Spiking Neural Networks Using Lessons From Deep Learning
Jason K. Eshraghian, Max Ward, Emre Neftci +6
The brain is the perfect place to look for inspiration to develop more efficient neural networks. The inner workings of our synapses and neurons provide a glimpse at what the futur…