3 citations · 3 across the 8 of their papers we have counts for
9 papers
PCoMoE: Shifting MoE Inference from Monolithic Expert Selection to Fine-Grained Path Composition
Ziyan Gan, Fangxin Liu, Chenyang Guan +10
Mixture-of-Experts (MoE) architectures scale Large Language Model (LLM) capacity efficiently by activating a sparse subset of experts per token. However, modern MoE inference remai…
CURE: Local Uncertainty Repair for Block-Parallel Speculative Decoding
Aofan Liu, Jingxiang Meng, Fangxin Liu +1
Speculative decoding mitigates the latency of sequential generation in autoregressive Large Language Models (LLMs) by interleaving draft generation with target verification. Howeve…
COSM: A Cooperative Scheduling Framework for Concurrent PIM and CPU Execution on Mobile Devices
Yilong Zhao, Fangxin Liu, Onur Mutlu +4
The development of on-device large language models (LLMs) is driven by the need for privacy and fast response times. Energy-intensive data transfer on mobile devices makes Processi…
Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference
Xuwen Zhou, Fangxin Liu, Chao Wang +5
Speculative decoding accelerates autoregressive generation by letting draft tokens bypass full verification, but conventional frameworks suffer from frequent false rejections, part…
HyperOffload: Graph-Driven Hierarchical Memory Management for Large Language Models on SuperNode Architectures
Fangxin Liu, Qinghua Zhang, Hanjing Shen +5
The rapid evolution of Large Language Models (LLMs) towards long-context reasoning and sparse architectures has pushed memory requirements far beyond the capacity of individual dev…
PUSHtap: PIM-based In-Memory HTAP with Unified Data Storage Format
Yilong Zhao, Mingyu Gao, Huanchen Zhang +5
Hybrid transaction/analytical processing (HTAP) is an emerging database paradigm that supports both online transaction processing (OLTP) and online analytical processing (OLAP) wor…
ASDR: Exploiting Adaptive Sampling and Data Reuse for CIM-based Instant Neural Rendering
Fangxin Liu, Haomin Li, Bowen Zhu +4
Neural Radiance Fields (NeRF) offer significant promise for generating photorealistic images and videos. However, existing mainstream neural rendering models often fall short in me…
Accelerating Sparse Transformer Inference on GPU
Wenhao Dai, Haodong Deng, Mengfei Rong +6
Large language models (LLMs) are popular around the world due to their powerful understanding capabilities. As the core component of LLMs, accelerating Transformer through parallel…
The Phantom of PCIe: Constraining Generative Artificial Intelligences for Practical Peripherals Trace Synthesizing
Zhibai Huang, Chen Chen, James Yen +9
Peripheral Component Interconnect Express (PCIe) is the de facto interconnect standard for high-speed peripherals and CPUs. The development of PCIe devices for emerging application…