5 citations · 5 across the 5 of their papers we have counts for
5 papers
A Full-Stack Performance Evaluation Infrastructure for 3D-DRAM-based LLM Accelerators
Cong Li, Chenhao Xue, Yi Ren +11
Large language models (LLMs) exhibit memory-intensive behavior during decoding, making it a key bottleneck in LLM inference. To accelerate decoding execution, hybrid-bonding-based…
SeerAttention-R: Sparse Attention Adaptation for Long Reasoning
Yizhao Gao, Shuming Guo, Shijie Cao +12
We introduce SeerAttention-R, a sparse attention framework specifically tailored for the long decoding of reasoning models. Extended from SeerAttention, SeerAttention-R retains the…
TileLang: A Composable Tiled Programming Model for AI Systems
Lei Wang, Yu Cheng, Yining Shi +8
Modern AI workloads rely heavily on optimized computing kernels for both training and inference. These AI kernels follow well-defined data-flow patterns, such as moving tiles betwe…
AttentionEngine: A Versatile Framework for Efficient Attention Mechanisms on Diverse Hardware Platforms
Feiyang Chen, Yu Cheng, Lei Wang +8
Transformers and large language models (LLMs) have revolutionized machine learning, with attention mechanisms at the core of their success. As the landscape of attention variants e…
Scaling Deep Learning Computation over the Inter-Core Connected Intelligence Processor with T10
Yiqi Liu, Yuqi Xue, Yu Cheng +4
As AI chips incorporate numerous parallelized cores to scale deep learning (DL) computing, inter-core communication is enabled recently by employing high-bandwidth and low-latency…