99 citations
- Purdue University West LafayetteUS3 papers
- University of Southern CaliforniaUS3 papers
- Microsoft (United States)US2 papers
- New York UniversityUS2 papers
- Advanced Micro Devices (United States)US1 paper
- AT4 wireless (Spain)ES1 paper
- Berkeley CollegeUS1 paper
- Duke UniversityUS1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- Electronics and Telecommunications Research InstituteKR1 paper
- Fraunhofer Institute for Telecommunications, Heinrich Hertz InstituteDE1 paper
- Georgia Institute of TechnologyUS1 paper
20 papers
Real Life Is Uncertain. Consensus Should Be Too!
Reginald Frank, Soujanya Ponnapalli, Octavio Lomeli +3
Modern distributed systems rely on consensus protocols to build a fault-tolerant-core upon which they can build applications. Consensus protocols are correct under a specific failu…
DynamiQ: Accelerating Gradient Synchronization using Compressed Multi-hop All-reduce
Wenchen Han, Shay Vargaftik, Michael Mitzenmacher +1
Multi-hop all-reduce is the de facto backbone of large model training. As the training scale increases, the network often becomes a bottleneck, motivating the reduction of the volu…
In-Network Collective Operations: Game Changer or Challenge for AI Workloads?
Torsten Hoefler, Mikhail Khalilov, Josiah Clark +9
This paper summarizes the opportunities of in-network collective operations (INC) for accelerated collective operations in AI workloads. We provide sufficient detail to make this i…
Reimagining RDMA Through the Lens of ML
Ertza Warraich, Ali Imran, Annus Zulfiqar +3
As distributed machine learning (ML) workloads scale to thousands of GPUs connected by ultra-high-speed inter-connects, tail latency in collective communication has emerged as a pr…
HONEYBEE: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning[Technical Report]
Hongbin Zhong, Matthew Lentz, Nina Narodytska +2
Enterprise deployments of vector databases require access control policies to protect sensitive data. These systems often implement access control through hybrid vector queries tha…
Coded Computing for Low-Latency Federated Learning over Wireless Edge Networks
Saurav Prakash, Sagar Dhakal, Mustafa Akdeniz +4
Federated learning enables training a global model from data located at the client nodes, without data sharing and moving client data to a centralized server. Performance of federa…