In-network Computing

SmartShuffle

Towards Accelerating Data Intensive Application’s Shuffle Process Using SmartNICs

RingLeader

Efficiently Offloading Intra-Server Orchestration to NICs

MTP

TCP is Harmful to In-Network Computing: Designing a Message-Oriented Transport Protocol (MTP)

ATP

In-network Aggregation for Multi-tenant Learning

PANIC

A High-Performance Programmable NIC for Multi-tenant Networks

Learning-Directed Systems

Darwin

Flexible Learning-based CDN Caching

Next-generation Cellular Networks

Slingshot

Resilient Baseband Processing in Virtualized RANs

Atlas

Enabling Resilience in Virtualized RANs

Serverless and Microservices

Copper Wire

Redesigning the control plane and data plane for service meshes

Medes

Memory Deduplication for Serverless and Microservices

Atoll

A Scalable Low-Latency Serverless Platform

Serverless NF

Serverless Network Functions

Systems for Machine Learning

A Lightweight Distributed Pre-Training Toolkit

Lowering the Pre-training Tax for Gradient-based Subset Training

Shockwave

Fair and Efficient Cluster Scheduling for Dynamic Adaptation in Machine Learning

Syndicate

Jointly Optimizing ML Collective Scheduling and Execution Planning

Themis

Fair and efficient GPU cluster scheduling for machine learning workloads

Older Projects

MLFabric

Network-accelerated distributed machine learning

Freeze Inference

Accelerating deep learning inference

Large-Scale Execution Engines and Cluster Schedulers

Fast, fair, and efficient execution of multiple analytics at scale

Big Data Analytics Under Resource Volatilities

Analytics in the face of data geo-distribution and extreme compute volatility

Data Centric Analytics Stacks

Enabling data-driven computation