From the 1 of 6 linked papers with an AI index.
6 papers
Why Do Prefetchers Fail? Let Agents Answer
Xiangfeng Sun, Ceyu Xu, Ningzhi Ai +3
Hardware prefetchers are crucial to processor performance, yet their design remains labor-intensive and expert-driven. Architects inspect execution and memory-access traces, identi…
VersaQ-3D: Architecture Support for Visual Geometry Grounded Transformers via Versatile Quantization
Yipu Zhang, Jintao Cheng, Xingyu Liu +8
The paper introduces VersaQ-3D, a co-designed quantization algorithm and reconfigurable accelerator that enables low‑bit (4‑bit) inference of Visual Geometry Grounded Transformers…
Cache-Resident LLM Inference in GB-Scale Last-Level Caches
Wanning Zhang, Tongzhou Gu, Marco Canini +2
Large language model (LLM) inference is increasingly dominated by data movement across the memory hierarchy. Recent 3D-stacked cache technologies have enabled GB-scale last-level c…
STS: Efficient Sparse Attention with Speculative Token Sparsity
Ceyu Xu, Jiangnan Yu, Yongji Wu +1
The quadratic complexity of attention imposes severe memory and computational bottlenecks on Large Language Model (LLM) inference. This challenge is particularly acute for emerging…
ICP: Exploiting Instruction Correlation for Prefetching Irregular Memory Accesses
Mengming Li, Chenlu Miao, Buqing Xu +7
Irregular memory accesses pose challenges for effective and efficient data prefetching. While temporal prefetchers have recently shown promise for irregular memory access patterns,…
A Scalable Architecture for Efficient Multi-bit Fully Homomorphic Encryption
Jiaao Ma, Ceyu Xu, Lisa Wu Wills
In the era of cloud computing, privacy-preserving computation offloading is crucial for safeguarding sensitive data. Fully Homomorphic Encryption (FHE) enables secure processing of…