Speaker: Phil Bernstein
Location: Soda 510
Date: November 1st, 2024
Time: 12pm-1pm PDT
Title: DDS: Data Processing with DPUs
Abstract:
A DPU is a network interface card (NIC) with programmable compute and memory resources. It sits on the system bus, PCIe, which is the fastest path to access SSDs, and it directly connects to the network. It therefore can process storage requests as soon as they arrive at the NIC, rather than passing them through to the host. DPUs are widely deployed in public clouds and will soon be ubiquitous.
In this talk, we’ll describe DPU-Optimized Disaggregated Storage (DDS), our software platform for offloading storage operations from a host storage server to a DPU. It reduces the cost and improves the performance of supporting a database service. DDS heavily uses DMA, zero-copy, and userspace I/O to minimize overhead and thereby improve throughput. It also introduces an offload engine that can directly execute storage requests on the DPU. For example, it can offload GetPage@LSN to the DPU of an Azure SQL Hyperscale page server. This removes all host CPU consumption (saving up to 17 cores), reduces latency by 70%, and increases throughput by 75%. This is joint work with Qizhen Zhang, Badrish Chandramouli, Jason Hu, and Yiming Zheng.
Bio:
Philip A. Bernstein is a Distinguished Scientist in the Data Systems Group in Microsoft Research. He has published over 200 papers and two books on the theory and implementation of database systems, especially on transaction processing and data integration, and has contributed to many database products. He is a Fellow of the ACM and AAAS, a winner of the E.F. Codd SIGMOD Innovations Award, and a member of the Washington State Academy of Sciences and the National Academy of Engineering. He received a B.S. degree from Cornell and M.Sc. and Ph.D. from University of Toronto.