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Open Source

Horovod v0.21: Optimizing Network Utilization with Local Gradient Aggregation and Grouped Allreduce

We originally open-sourced Horovod in 2017, and since then it has grown to become the standard solution in industry for scaling deep learning training...

Revolutionizing Money Movements at Scale with Strong Data Consistency

Uber as a platform invites its users to leverage it, earn from it, and be delighted by it. Serving more than 18 million requests...

Fiber: Distributed Computing for AI Made Simple

Project Homepage: GitHub Over the past several years, increasing processing power of computing machines has led to an increase in machine learning advances. More and...

Uber Visualization Highlights: How Urban Symphony Adds an Audio Dimension to Visualization

As part of Uber Visualization's all-team hackathon, we built Urban Symphony, an Uber Movement visualization that adds an audio component to traffic speed patterns.

Enabling Collaboration through Open Source: Highlights from Uber Open Summit Sofia 2019

At the Uber Open Summit Sofia 2019, we showcased how open source technologies are driving the future of artificial intelligence, site reliability, and other domains.

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series...

Part of Uber's open source M3 metrics system, our query engine can support real-time, large-scale computation and multiple query languages.

Uber Joins the Linux Foundation as a Gold Member

Announced during the Uber Open Summit 2018, we extend our commitment to open source by joining the Linux Foundation as a Gold Member.

NVIDIA: Accelerating Deep Learning with Uber’s Horovod

Horovod, Uber's open source distributed deep learning system, enables NVIDIA to scale model training from one to eight GPUs for their self-driving sensing and perception technologies.

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