135 citations · 161 across the 6 of their papers we have counts for
9 papers
CAKE: Compiler-Agent Co-Design for Frontier Kernel Evolution
Zihao Ye, Yingyi Huang, Hongyi Jin +11
GPU kernel agents and GPU programming languages have advanced separately, leaving expert kernels difficult to reproduce. Agents usually treat the compiler as a fixed black box and…
GC3: An Optimizing Compiler for GPU Collective Communication
Meghan Cowan, Saeed Maleki, Madanlal Musuvathi +2
Machine learning models made up of millions or billions of parameters are trained and served on large multi-GPU systems. As models grow in size and execute on more GPUs, the collec…
TACCL: Guiding Collective Algorithm Synthesis using Communication Sketches
Aashaka Shah, Vijay Chidambaram, Meghan Cowan +6
Machine learning models are increasingly being trained across multiple GPUs and servers. In this setting, data is transferred between GPUs using communication collectives such as A…
Analysis and Mitigations of Reverse Engineering Attacks on Local Feature Descriptors
Deeksha Dangwal, Vincent T. Lee, Hyo Jin Kim +9
As autonomous driving and augmented reality evolve, a practical concern is data privacy. In particular, these applications rely on localization based on user images. The widely ado…
SoK: Opportunities for Software-Hardware-Security Codesign for Next Generation Secure Computing
Deeksha Dangwal, Meghan Cowan, Armin Alaghi +3
Users are demanding increased data security. As a result, security is rapidly becoming a first-order design constraint in next generation computing systems. Researchers and practit…
Porcupine: A Synthesizing Compiler for Vectorized Homomorphic Encryption
Meghan Cowan, Deeksha Dangwal, Armin Alaghi +3
Homomorphic encryption (HE) is a privacy-preserving technique that enables computation directly on encrypted data. Despite its promise, HE has seen limited use due to performance o…
Automating Generation of Low Precision Deep Learning Operators
Meghan Cowan, Thierry Moreau, Tianqi Chen +1
State of the art deep learning models have made steady progress in the fields of computer vision and natural language processing, at the expense of growing model sizes and computat…
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning
Tianqi Chen, Thierry Moreau, Ziheng Jiang +9
There is an increasing need to bring machine learning to a wide diversity of hardware devices. Current frameworks rely on vendor-specific operator libraries and optimize for a narr…
Exploring Computation-Communication Tradeoffs in Camera Systems
Amrita Mazumdar, Thierry Moreau, Sung Kim +5
Cameras are the defacto sensor. The growing demand for real-time and low-power computer vision, coupled with trends towards high-efficiency heterogeneous systems, has given rise to…