Keren Zhou
Keren Zhou
Home
Experience
Projects
Featured
Publications
Talks
Students
Tags
News
Light
Dark
Automatic
1
SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform
Tensor multiplication with learned weight matrices is the fundamental building block in deep learning models. These matrices can often …
Aditya Desai
,
Kimia Saedi
,
Apoorv Walia
,
Jihyeong Lee
,
Keren Zhou
,
Anshumali Shrivastava
Cite
Project
Centimani: Enabling Fast AI Accelerator Selection for DNN Training with a Novel Performance Predictor
For an extended period, graphics processing units (GPUs) have stood as the exclusive choice for training deep neural network (DNN) …
Zhen Xie
,
Murali Emani
,
Xiaodong Yu
,
Dingwen Tao
,
Xin He
,
Pengfei Su
,
Keren Zhou
,
Venkatram Vishwanath
Cite
Project
URL
FASTEN: Fast GPU-accelerated Segmented Matrix Multiplication for Heterogenous Graph Neural Networks
This paper introduces FASTEN, a cutting-edge library developed to address the computational challenges inherent in Heterogeneous Graph …
Keren Zhou
,
Karthik Ganapathi Subramanian
,
Po-Hsun Lin
,
Matthias Fey
,
Binqian Yin
,
Jiajia Li
Cite
Project
DOI
URL
PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation
This paper introduces two extensions to the popular PyTorch machine learning framework, TorchDynamo and TorchInductor, which implement …
Jason Ansel
,
Edward Yang
,
Horace He
,
Natalia Gimelshein
,
Animesh Jain
,
Michael Voznesensky
,
Bin Bao
,
Peter Bell
,
David Berard
,
Evgeni Burovski
,
Geeta Chauhan
,
Anjali Chourdia
,
Will Constable
,
Alban Desmaison
,
Zachary DeVito
,
Elias Ellison
,
Will Feng
,
Jiong Gong
,
Michael Gschwind
,
Brian Hirsh
,
Sherlock Huang
,
Kshiteej Kalambarkar
,
Laurent Kirsch
,
Michael Lazos
,
Mario Lezcano
,
Yanbo Liang
,
Jason Liang
,
Yinghai Lu
,
C. K. Luk
,
Bert Maher
,
Yunjie Pan
,
Christian Puhrsch
,
Matthias Reso
,
Mark Saroufim
,
Marcos Yukio Siraichi
,
Helen Suk
,
Shunting Zhang
,
Michael Suo
,
Phil Tillet
,
Xu Zhao
,
Eikan Wang
,
Keren Zhou
,
Richard Zou
,
Xiaodong Wang
,
Ajit Mathews
,
William Wen
,
Gregory Chanan
,
Peng Wu
,
Soumith Chintala
Cite
Project
DOI
URL
Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing
Advancements in deep learning are often associated with increasing model sizes. Training and deploying large models require …
Aditya Desai
,
Keren Zhou
,
Anshumali Shrivastava
Cite
Project
URL
DrGPUM: Guiding Memory Optimization for GPU-Accelerated Applications
GPUs are widely used in today’s computing platforms to accelerate applications in various domains. However, scarce GPU memory resources …
Mao Lin
,
Keren Zhou
,
Pengfei Su
Cite
Project
DOI
URL
Low Overhead and Context Sensitive Profiling of GPU-Accelerated Applications
As we near the end of Moore’s law scaling, the next-generation computing platforms are increasingly exploring heterogeneous …
Keren Zhou
,
Jonathon Anderson
,
Xiaozhu Meng
,
John Mellor-Crummey
Cite
Project
DOI
URL
ValueExpert: Exploring Value Patterns in GPU-Accelerated Applications
General-purpose GPUs have become common in modern computing systems to accelerate applications in many domains, including machine …
Keren Zhou
,
Yueming Hao
,
John Mellor-Crummey
,
Xiaozhu Meng
,
Xu Liu
Cite
Project
DOI
URL
GPA: A GPU Performance Advisor Based on Instruction Sampling
Developing efficient GPU kernels can be difficult because of the complexity of GPU architectures and programming models. Existing …
Keren Zhou
,
Xiaozhu Meng
,
Ryuichi Sai
,
John Mellor-Crummey
Cite
Project
DOI
URL
Measurement and Analysis of GPU-Accelerated OpenCL Computations on Intel GPUs
Graphics Processing Units (GPUs) have become a key technology for accelerating node performance in supercomputers, including the US …
Aaron Thomas Cherian
,
Keren Zhou
,
Dejan Grubisic
,
Xiaozhu Meng
,
John Mellor-Crummey
Cite
Project
DOI
URL
»
Cite
×