1 citations · 1 across the 7 of their papers we have counts for
7 papers
WaferTrans: Enabling IOMMU-free Distributed Virtual Address Translation for Wafer-scale GPUs
Xinru Tang, Jingxiang Hou, Guanghong Wu +2
Wafer-scale GPUs (WSGs) provide sufficient on-wafer bandwidth to make near-lossless Unified Memory feasible. However, existing designs still rely on a CPU-IOMMU to translate remote…
Designing Spatial Architectures for Sparse Attention: STAR Accelerator via Cross-Stage Tiling
Huizheng Wang, Taiquan Wei, Hongbin Wang +6
Large language models (LLMs) rely on self-attention for contextual understanding, demanding high-throughput inference and large-scale token parallelism (LTPP). Existing dynamic spa…
MoEntwine: Unleashing the Potential of Wafer-scale Chips for Large-scale Expert Parallel Inference
Xinru Tang, Jingxiang Hou, Dingcheng Jiang +9
As large language models (LLMs) continue to scale up, mixture-of-experts (MoE) has become a common technology in SOTA models. MoE models rely on expert parallelism (EP) to alleviat…
Tackling the Dynamicity in a Production LLM Serving System with SOTA Optimizations via Hybrid Prefill/Decode/Verify Scheduling on Efficient Meta-kernels
Mingcong Song, Xinru Tang, Fengfan Hou +9
Meeting growing demands for low latency and cost efficiency in production-grade large language model (LLM) serving systems requires integrating advanced optimization techniques. Ho…
SOFA: A Compute-Memory Optimized Sparsity Accelerator via Cross-Stage Coordinated Tiling
Huizheng Wang, Jiahao Fang, Xinru Tang +9
Benefiting from the self-attention mechanism, Transformer models have attained impressive contextual comprehension capabilities for lengthy texts. The requirements of high-throughp…
Efficient Orchestrated AI Workflows Execution on Scale-out Spatial Architecture
Jinyi Deng, Xinru Tang, Zhiheng Yue +8
Given the increasing complexity of AI applications, traditional spatial architectures frequently fall short. Our analysis identifies a pattern of interconnected, multi-faceted task…
Wafer-scale Computing: Advancements, Challenges, and Future Perspectives
Yang Hu, Xinhan Lin, Huizheng Wang +12
Nowadays, artificial intelligence (AI) technology with large models plays an increasingly important role in both academia and industry. It also brings a rapidly increasing demand f…