2 citations · 2 across the 4 of their papers we have counts for
5 papers
FlashT2S: GPU-Accelerated Tensor-to-Spike Conversion Operators for Heterogeneous Neuromorphic LLM Backends
Rongyuan Guo, Haotian Wang, Yufeng Zhang +2
Artificial intelligence faces two growing challenges: computational bottlenecks and energy inefficiency inherent to the von Neumann architecture. Neuromorphic computing offers a pr…
A-IO: Adaptive Inference Orchestration for Memory-Bound NPUs
Chen Zhang, Yan Ding, Haotian Wang +3
During the deployment of Large Language Models (LLMs), the autoregressive decoding phase on heterogeneous NPU platforms (e.g., Ascend 910B) faces severe memory-bound challenges. Th…
MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations
Xianyong Xu, Yuanjun Zuo, Zhihong Huang +4
Time series forecasting is vital across many domains, yet existing models struggle with fixed-length inputs and inadequate multi-scale modeling. We propose MR-CDM, a framework comb…
BLITZSCALE: Fast and Live Large Model Autoscaling with O(1) Host Caching
Dingyan Zhang, Haotian Wang, Yang Liu +4
Model autoscaling is the key mechanism to achieve serverless model-as-a-service, but it faces a fundamental trade-off between scaling speed and storage/memory usage to cache parame…
Transactional Indexes on (RDMA or CXL-based) Disaggregated Memory with Repairable Transaction
Xingda Wei, Haotian Wang, Tianxia Wang +4
The failure atomic and isolated execution of clients operations is a default requirement for a system that serve multiple loosely coupled clients at a server. However, disaggregate…