3 citations · 5 across the 6 of their papers we have counts for
6 papers
SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference
Shanghao Liu, Renze Chen, Size Zheng +4
Video diffusion transformers (vDiTs) generate high quality but pay quadratic self-attention cost, making inference prohibitive at video-token scales. The challenge is input-adaptiv…
DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs
Size Zheng, Xuegui Zheng, Hanshi Sun +16
The scaling of large language models (LLMs) is currently bottlenecked by the rigidity of distributed programming. While high-performance libraries like CuBLAS and NCCL provide opti…
Aquas: Enhancing Domain Specialization through Holistic Hardware-Software Co-Optimization based on MLIR
Yuyang Zou, Youwei Xiao, Chenyun Yin +6
Application-Specific Instruction-Set Processors (ASIPs) built on the RISC-V architecture offer specialization opportunities for various applications. Existing frameworks are largel…
Triton-distributed: Programming Overlapping Kernels on Distributed AI Systems with the Triton Compiler
Size Zheng, Wenlei Bao, Qi Hou +19
In this report, we propose Triton-distributed, an extension of existing Triton compiler, to overcome the programming challenges in distributed AI systems. Triton-distributed is the…
MCUBERT: Memory-Efficient BERT Inference on Commodity Microcontrollers
Zebin Yang, Renze Chen, Taiqiang Wu +5
In this paper, we propose MCUBERT to enable language models like BERT on tiny microcontroller units (MCUs) through network and scheduling co-optimization. We observe the embedding…
vMCU: Coordinated Memory Management and Kernel Optimization for DNN Inference on MCUs
Size Zheng, Renze Chen, Meng Li +3
IoT devices based on microcontroller units (MCU) provide ultra-low power consumption and ubiquitous computation for near-sensor deep learning models (DNN). However, the memory of M…