273 citations · 379 across the 9 of their papers we have counts for
9 papers
In-Place Updates of a Graph Index for Streaming Approximate Nearest Neighbor Search
Haike Xu, Magdalen Dobson Manohar, Philip A. Bernstein +3
Indices for approximate nearest neighbor search (ANNS) are a basic component for information retrieval and widely used in database, search, recommendation and RAG systems. In these…
Distributed Speculative Execution for Resilient Cloud Applications
Tianyu Li, Badrish Chandramouli, Philip A. Bernstein +1
Fault-tolerance is critically important in highly-distributed modern cloud applications. Solutions such as Temporal, Azure Durable Functions, and Beldi hide fault-tolerance complex…
DDS: DPU-optimized Disaggregated Storage [Extended Report]
Qizhen Zhang, Philip Bernstein, Badrish Chandramouli +2
This extended report presents DDS, a novel disaggregated storage architecture enabled by emerging networking hardware, namely DPUs (Data Processing Units). DPUs can optimize the la…
From FASTER to F2: Evolving Concurrent Key-Value Store Designs for Large Skewed Workloads
Konstantinos Kanellis, Badrish Chandramouli, Ted Hart +1
Modern large-scale services such as search engines, messaging platforms, and serverless functions, rely on key-value (KV) stores to maintain high performance at scale. When such se…
Redy: Remote Dynamic Memory Cache
Qizhen Zhang, Philip A. Bernstein, Daniel S. Berger +1
Redy is a cloud service that provides high performance caches using RDMA-accessible remote memory. An application can customize the performance of each cache with a service level o…
Achieving High Throughput and Elasticity in a Larger-than-Memory Store
Chinmay Kulkarni, Badrish Chandramouli, Ryan Stutsman
Millions of sensors, mobile applications and machines now generate billions of events. Specialized many-core key-value stores (KVSs) can ingest and index these events at high rates…
Qd-tree: Learning Data Layouts for Big Data Analytics
Zongheng Yang, Badrish Chandramouli, Chi Wang +6
Corporations today collect data at an unprecedented and accelerating scale, making the need to run queries on large datasets increasingly important. Technologies such as columnar b…
ALEX: An Updatable Adaptive Learned Index
Jialin Ding, Umar Farooq Minhas, Jia Yu +9
Recent work on "learned indexes" has changed the way we look at the decades-old field of DBMS indexing. The key idea is that indexes can be thought of as "models" that predict the…
Streaming Algorithms for Pattern Discovery over Dynamically Changing Event Sequences
Debprakash Patnaik, Naren Ramakrishnan, Srivatsan Laxman +1
Discovering frequent episodes over event sequences is an important data mining task. In many applications, events constituting the data sequence arrive as a stream, at furious rate…