54k citations · 60.1k across the 24 of their papers we have counts for
6 papers · 1 filter
ADARES: Adaptive Resource Management for Virtual Machines
Ignacio Cano, Lequn Chen, Pedro Fonseca +5
Virtual execution environments allow for consolidation of multiple applications onto the same physical server, thereby enabling more efficient use of server resources. However, use…
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…
Relay: A New IR for Machine Learning Frameworks
Jared Roesch, Steven Lyubomirsky, Logan Weber +4
Machine learning powers diverse services in industry including search, translation, recommendation systems, and security. The scale and importance of these models require that they…
A Hardware-Software Blueprint for Flexible Deep Learning Specialization
Thierry Moreau, Tianqi Chen, Luis Vega +8
Specialized Deep Learning (DL) acceleration stacks, designed for a specific set of frameworks, model architectures, operators, and data types, offer the allure of high performance…
Learning to Optimize Tensor Programs
Tianqi Chen, Lianmin Zheng, Eddie Yan +5
We introduce a learning-based framework to optimize tensor programs for deep learning workloads. Efficient implementations of tensor operators, such as matrix multiplication and hi…
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…