Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
IEEE International Conference on Data Engineering (ICDE)
Presto is an open source distributed query engine that supports much of the SQL analytics workload at Facebook. Presto is designed to be adaptive, flexible, and extensible. It supports a wide variety of use cases with diverse characteristics. These range from user-facing reporting applications with sub-second latency requirements to multi-hour ETL jobs that aggregate or join terabytes of data. Presto’s Connector API allows plugins to provide a high performance I/O interface to dozens of data sources, including Hadoop data warehouses, RDBMSs, NoSQL systems, and stream processing systems. In this paper, we outline a selection of use cases that Presto supports at Facebook. We then describe its architecture and implementation, and call out features and performance optimizations that enable it to support these use cases. Finally, we present performance results that demonstrate the impact of our main design decisions.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Lisa Rivalin, Andrew Grier, Tobias Tiecke, Chi Zhou, Doris Gao, Prakriti Choudhury, John Fabian
Nadia Alshahwan, Mark Harman, Alexandru Marginean