10 citations · 18 across the 4 of their papers we have counts for
4 papers
WebLLM: A High-Performance In-Browser LLM Inference Engine
Charlie F. Ruan, Yucheng Qin, Akaash R. Parthasarathy +11
Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-grade GPUs and cloud-based inference, the…
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning
Zihao Ye, Ruihang Lai, Junru Shao +2
Sparse tensors are rapidly becoming critical components of modern deep learning workloads. However, developing high-performance sparse operators can be difficult and tedious, and e…
TensorIR: An Abstraction for Automatic Tensorized Program Optimization
Siyuan Feng, Bohan Hou, Hongyi Jin +8
Deploying deep learning models on various devices has become an important topic. The wave of hardware specialization brings a diverse set of acceleration primitives for multi-dimen…
Tensor Program Optimization with Probabilistic Programs
Junru Shao, Xiyou Zhou, Siyuan Feng +7
Automatic optimization for tensor programs becomes increasingly important as we deploy deep learning in various environments, and efficient optimization relies on a rich search spa…