Publications (6)
2018 Low-Power Image Recognition Challenge
Sergei Alyamkin, Matthew Ardi, Achille Brighton +38
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technolog…
RED: A ReRAM-based Deconvolution Accelerator
Zichen Fan, Ziru Li, Bing Li +3
Deconvolution has been widespread in neural networks. For example, it is essential for performing unsupervised learning in generative adversarial networks or constructing fully con…
Low-Power Computer Vision: Status, Challenges, Opportunities
Sergei Alyamkin, Matthew Ardi, Alexander C. Berg +41
Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have become the primary computing platforms for millions of people. In addition to mobile…
SQ-DM: Accelerating Diffusion Models with Aggressive Quantization and Temporal Sparsity
Zichen Fan, Steve Dai, Rangharajan Venkatesan +2
Diffusion models have gained significant popularity in image generation tasks. However, generating high-quality content remains notably slow because it requires running model infer…
ConSmax: Hardware-Friendly Alternative Softmax with Learnable Parameters
Shiwei Liu, Guanchen Tao, Yifei Zou +7
The self-attention mechanism distinguishes transformer-based large language models (LLMs) apart from convolutional and recurrent neural networks. Despite the performance improvemen…
Efficient Computation Sharing for Multi-Task Visual Scene Understanding
Sara Shoouri, Mingyu Yang, Zichen Fan +1
Solving multiple visual tasks using individual models can be resource-intensive, while multi-task learning can conserve resources by sharing knowledge across different tasks. Despi…