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08/14/2023
Symphony: Optimized Model Serving using Centralized Orchestration
The orchestration of deep neural network (DNN) model inference on GPU cl...
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05/29/2023
Bandwidth Optimal Pipeline Schedule for Collective Communication
We present a strongly polynomial-time algorithm to generate bandwidth op...
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05/18/2023
TSoR: TCP Socket over RDMA Container Network for Cloud Native Computing
Cloud-native containerized applications constantly seek high-performance...
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07/02/2022
Dissecting Service Mesh Overheads
Service meshes play a central role in the modern application ecosystem b...
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02/07/2022
Optimal Direct-Connect Topologies for Collective Communications
We consider the problem of distilling optimal network topologies for col...
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09/16/2021
Disaggregating and Consolidating Network Functionalities with SuperNIC
Resource disaggregation has gained huge popularity in recent years. Exis...
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05/28/2021
Cloud Collectives: Towards Cloud-aware Collectives forML Workloads with Rank Reordering
ML workloads are becoming increasingly popular in the cloud. Good cloud ...
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05/22/2021
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
The learning rate (LR) schedule is one of the most important hyper-param...
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11/29/2020
Srift: Swift and Thrift Cloud-Based Distributed Training
Cost-efficiency and training time are primary concerns in cloud-based di...
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08/14/2020
Making Distributed Mobile Applications SAFE: Enforcing User Privacy Policies on Untrusted Applications with Secure Application Flow Enforcement
Today's mobile devices sense, collect, and store huge amounts of persona...
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01/22/2020
Talek: Private Group Messaging with Hidden Access Patterns
Talek is a private group messaging system that sends messages through po...
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04/24/2019
DeepSense: Enabling Carrier Sense in Low-Power Wide Area Networks Using Deep Learning
The last few years have seen the proliferation of low-power wide area ne...
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02/22/2019
Scaling Distributed Machine Learning with In-Network Aggregation
Training complex machine learning models in parallel is an increasingly ...
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12/05/2018
ADARES: Adaptive Resource Management for Virtual Machines
Virtual execution environments allow for consolidation of multiple appli...
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07/11/2018
VTA: An Open Hardware-Software Stack for Deep Learning
Hardware acceleration is an enabler for ubiquitous and efficient deep le...
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06/21/2018
Revisiting Network Support for RDMA
The advent of RoCE (RDMA over Converged Ethernet) has led to a significa...
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05/21/2018
Learning to Optimize Tensor Programs
We introduce a learning-based framework to optimize tensor programs for ...
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05/21/2018
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training
Distributed deep neural network (DDNN) training constitutes an increasin...
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04/18/2018
Volur: Concurrent Edge/Core Route Control in Data Center Networks
A perennial question in computer networks is where to place functionalit...
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02/12/2018
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning
There is an increasing need to bring machine learning to a wide diversit...
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02/12/2018
TVM: End-to-End Optimization Stack for Deep Learning
Scalable frameworks, such as TensorFlow, MXNet, Caffe, and PyTorch drive...
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01/30/2018
Parameter Hub: High Performance Parameter Servers for Efficient Distributed Deep Neural Network Training
Most work in the deep learning systems community has focused on faster i...
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11/20/2016