As Large Language Models (LLMs) become essential in privacy-sensitive sectors like hospitals and government agencies, the on-premise LLM servers offer a cost-effective and secure alternative to public cloud services. However, these resource-constrained servers struggle to guarantee heterogeneous Service Level Objective...
Ze-Shen Zhang, Han Zhao, Wei-Hao Cui et al.· 0 citations
Deltoris is presented, an algorithm-hardware co-design framework for efficient diffusion-based VLA inference that exploits the temporal similarity of consecutive inputs and proposes a temporal-aware bit-sparsity algorithm that computes only the differences between consecutive inputs, eliminating redundant bit-level ope...
Zheng Liu, Zeyu Guo, Zi-Han Liu et al.· 1 citation
Atlas is presented, an on device city scale 3DGS rendering framework that enables scalable rendering without runtime Internet access and proposes temporal aware LoD search and stereo rasterization to avoid redundant computation in VR.
He Zhu, Zheng Liu, Xingyang Li et al.· 0 citations
Kaleido is presented, an algorithm hardware codesign that accelerates all operations in vDiTs by exploiting channel-wise spatiotemporal correlations in latent space and skips redundant computations by reusing partial results while preserving higher generative quality than prior methods.
Wen-Xuan Miao, Haosong Liu, Weiming Hu et al.· arXiv.org· 1 citation
DSTAR, a software-hardware co-design framework that accelerates DiT inference by reducing spatial and temporal redundancy and incorporates a sparse attention reuse mechanism to minimize redundant computation in attention layers, and design a specialized hardware accelerator which achieves high efficiency in both latenc...
Chi Zhang, Jieru Zhao, Yu Feng et al.· arXiv.org· 2 citations
This work proposes FIBER, a new architecture that extends the GPU SIMT (single instruction, multiple thread) model, and extends the ISA, microarchitecture, and compiler to realize shared-register addressing, conflict-free operand delivery, and fiber-based program mapping.
Zi-Han Liu, Jingwen Leng, Yang-Jie Zhou et al.· 0 citations
This work proposes GPU-Tile-Sim, a tile-centric GPU simulation framework for LLM hardware-software co-design that represents kernel execution as a warp-level tile graph whose nodes capture tile-level operations and whose edges encode data and ordering constraints.
