21 citations · 39 across the 5 of their papers we have counts for
5 papers
CHIME: A Case for Efficient Long-Context Attention-FC Disaggregated Inference with DIMM-PIM
Qingyuan Liu, Liyan Chen, Haocheng Wang +6
Attention-FC Disaggregated (AFD) LLM inference systems offload memory-bound Attention operations to memory-rich accelerators (e.g., CPUs, HBM-PIM) while retaining compute-bound Ful…
LUT Tensor Core: A Software-Hardware Co-Design for LUT-Based Low-Bit LLM Inference
Zhiwen Mo, Lei Wang, Jianyu Wei +8
Large Language Model (LLM) inference becomes resource-intensive, prompting a shift toward low-bit model weights to reduce the memory footprint and improve efficiency. Such low-bit…
RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN
Yilong Zhao, Li Jiang, Mingyu Gao +6
The second-order training methods can converge much faster than first-order optimizers in DNN training. This is because the second-order training utilizes the inversion of the seco…
DNN Training Acceleration via Exploring GPGPU Friendly Sparsity
Zhuoran Song, Yihong Xu, Han Li +3
The training phases of Deep neural network~(DNN) consumes enormous processing time and energy. Compression techniques utilizing the sparsity of DNNs can effectively accelerate the…
CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction
Zhuoran Song, Yihong Xu, Zhezhi He +3
Vision transformer (ViT) has achieved competitive accuracy on a variety of computer vision applications, but its computational cost impedes the deployment on resource-limited mobil…