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20232026
most citedWafer-scale Computing: Advancements, Challenges, and Future Perspectives

1 citations · 1 across the 11 of their papers we have counts for

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cs.AR2026

Fovea: Physical-Implication-Aware Wafer-Scale DSE with Decision-Domain-Guided Cross-Fidelity Refinement

Jinxi Li, Huizheng Wang, Jinyi Deng +2

Modern pre-silicon design-space exploration (DSE) follows a coarse-to-fine workflow: low-cost evaluators screen candidate spaces, while detailed evaluation is reserved for a shortl…

cs.AR2026

MOCAP: Wafer-Scale-Chip-Oriented Memory-Orchestrated Chunked Pipelining Framework for Prefill-Only LLM Inference

Zichuan Wang, Huizheng Wang, Yuheng Xiao +6

Large language models (LLMs) are increasingly used in prefill-only workloads, where end-to-end latency is dominated by the prefill phase. For long-context prefill, communication ov…

cs.AR2025

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…

cs.AR2025

TEMP: A Memory Efficient Physical-aware Tensor Partition-Mapping Framework on Wafer-scale Chips

Huizheng Wang, Taiquan Wei, Zichuan Wang +8

Large language models (LLMs) demand significant memory and computation resources. Wafer-scale chips (WSCs) provide high computation power and die-to-die (D2D) bandwidth but face a…

cs.AR2025

MCBP: A Memory-Compute Efficient LLM Inference Accelerator Leveraging Bit-Slice-enabled Sparsity and Repetitiveness

Huizheng Wang, Zichuan Wang, Zhiheng Yue +8

Large language models (LLMs) face significant inference latency due to inefficiencies in GEMM operations, weight access, and KV cache access, especially in real-time scenarios. Thi…

cs.AR2024

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…

cs.AR2023★ 1 cited

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…