382 citations · 1.6k across the 39 of their papers we have counts for
42 papers
FactorJoin: A New Cardinality Estimation Framework for Join Queries
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh +2
Cardinality estimation is one of the most fundamental and challenging problems in query optimization. Neither classical nor learning-based methods yield satisfactory performance wh…
Coded Transaction Broadcasting for High-throughput Blockchains
Lei Yang, Yossi Gilad, Mohammad Alizadeh
High-throughput blockchains require efficient transaction broadcast mechanisms that can deliver transactions to most network nodes with low bandwidth overhead and latency. Existing…
Scalable Tail Latency Estimation for Data Center Networks
Kevin Zhao, Prateesh Goyal, Mohammad Alizadeh +1
In this paper, we consider how to provide fast estimates of flow-level tail latency performance for very large scale data center networks. Network tail latency is often a crucial m…
Optimal Congestion Control for Time-varying Wireless Links
Prateesh Goyal, Mohammad Alizadeh, Thomas E. Anderson
Modern networks exhibit a high degree of variability in link rates. Cellular network bandwidth inherently varies with receiver motion and orientation, while class-based packet sche…
Efficient Strong Scaling Through Burst Parallel Training
Seo Jin Park, Joshua Fried, Sunghyun Kim +2
As emerging deep neural network (DNN) models continue to grow in size, using large GPU clusters to train DNNs is becoming an essential requirement to achieving acceptable training…
Updating Street Maps using Changes Detected in Satellite Imagery
Favyen Bastani, Songtao He, Satvat Jagwani +5
Accurately maintaining digital street maps is labor-intensive. To address this challenge, much work has studied automatically processing geospatial data sources such as GPS traject…
Throughput-Fairness Tradeoffs in Mobility Platforms
Arjun Balasingam, Karthik Gopalakrishnan, Radhika Mittal +5
This paper studies the problem of allocating tasks from different customers to vehicles in mobility platforms, which are used for applications like food and package delivery, rides…
Efficient Video Compression via Content-Adaptive Super-Resolution
Mehrdad Khani, Vibhaalakshmi Sivaraman, Mohammad Alizadeh
Video compression is a critical component of Internet video delivery. Recent work has shown that deep learning techniques can rival or outperform human-designed algorithms, but the…
TagMe: GPS-Assisted Automatic Object Annotation in Videos
Songtao He, Favyen Bastani, Mohammad Alizadeh +4
Training high-accuracy object detection models requires large and diverse annotated datasets. However, creating these data-sets is time-consuming and expensive since it relies on h…
SWP: Microsecond Network SLOs Without Priorities
Kevin Zhao, Prateesh Goyal, Mohammad Alizadeh +1
The increasing use of cloud computing for latency-sensitive applications has sparked renewed interest in providing tight bounds on network tail latency. Achieving this in practice…
The Effect of Network Topology on Credit Network Throughput
Vibhaalakshmi Sivaraman, Weizhao Tang, Shaileshh Bojja Venkatakrishnan +2
Credit networks rely on decentralized, pairwise trust relationships (channels) to exchange money or goods. Credit networks arise naturally in many financial systems, including the…
Flow-Loss: Learning Cardinality Estimates That Matter
Parimarjan Negi, Ryan Marcus, Andreas Kipf +4
Previous approaches to learned cardinality estimation have focused on improving average estimation error, but not all estimates matter equally. Since learned models inevitably make…
Cortex: Harnessing Correlations to Boost Query Performance
Vikram Nathan, Jialin Ding, Tim Kraska +1
Databases employ indexes to filter out irrelevant records, which reduces scan overhead and speeds up query execution. However, this optimization is only available to queries that f…
Site-to-Site Internet Traffic Control
Frank Cangialosi, Akshay Narayan, Prateesh Goyal +3
Queues allow network operators to control traffic: where queues build, they can enforce scheduling and shaping policies. In the Internet today, however, there is a mismatch between…
Real-world Video Adaptation with Reinforcement Learning
Hongzi Mao, Shannon Chen, Drew Dimmery +5
Client-side video players employ adaptive bitrate (ABR) algorithms to optimize user quality of experience (QoE). We evaluate recently proposed RL-based ABR methods in Facebook's we…
Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding
Songtao He, Favyen Bastani, Satvat Jagwani +6
Inferring road graphs from satellite imagery is a challenging computer vision task. Prior solutions fall into two categories: (1) pixel-wise segmentation-based approaches, which pr…
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads
Jialin Ding, Vikram Nathan, Mohammad Alizadeh +1
Filtering data based on predicates is one of the most fundamental operations for any modern data warehouse. Techniques to accelerate the execution of filter expressions include clu…
Real-Time Video Inference on Edge Devices via Adaptive Model Streaming
Mehrdad Khani, Pouya Hamadanian, Arash Nasr-Esfahany +1
Real-time video inference on edge devices like mobile phones and drones is challenging due to the high computation cost of Deep Neural Networks. We present Adaptive Model Streaming…
Learned Garbage Collection
Lujing Cen, Ryan Marcus, Hongzi Mao +3
Several programming languages use garbage collectors (GCs) to automatically manage memory for the programmer. Such collectors must decide when to look for unreachable objects to fr…
Bao: Learning to Steer Query Optimizers
Ryan Marcus, Parimarjan Negi, Hongzi Mao +3
Query optimization remains one of the most challenging problems in data management systems. Recent efforts to apply machine learning techniques to query optimization challenges hav…
RoadTagger: Robust Road Attribute Inference with Graph Neural Networks
Songtao He, Favyen Bastani, Satvat Jagwani +7
Inferring road attributes such as lane count and road type from satellite imagery is challenging. Often, due to the occlusion in satellite imagery and the spatial correlation of ro…
Learning Multi-dimensional Indexes
Vikram Nathan, Jialin Ding, Mohammad Alizadeh +1
Scanning and filtering over multi-dimensional tables are key operations in modern analytical database engines. To optimize the performance of these operations, databases often crea…
Inferring and Improving Street Maps with Data-Driven Automation
Favyen Bastani, Songtao He, Satvat Jagwani +7
Street maps are a crucial data source that help to inform a wide range of decisions, from navigating a city to disaster relief and urban planning. However, in many parts of the wor…
Practical Low Latency Proof of Work Consensus
Lei Yang, Xuechao Wang, Vivek Bagaria +5
Bitcoin is the first fully-decentralized permissionless blockchain protocol to achieve a high level of security, but at the expense of poor throughput and latency. Scaling the perf…