The DLRover version used in this article is 0.3.7 1. DLRover Operator 1.1 Starting the ElasticJob and ScalePlan Controllers Implementation code: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 // 创建 ElasticJob 的控制器 if err = controllers.NewElasticJobReconciler(mgr, masterImage).SetupWithManager(mgr); err

1. Product Lines GeForce Aimed at gamers, offering powerful graphics processing capabilities and advanced gaming technologies. Common ones include the NVIDIA GTX series, the high-end RTX series, and the Titan series. Quadro Aimed at the professional market, such as designers, engineers, scientists, and content creators. Common ones include the Quadro P series and the high-end Quadro RTX series.

1. Parameter Server Architecture In the Parameter Server architecture, the nodes in the cluster are divided into two categories: parameter server nodes (Parameter Server) and worker server nodes (Worker). 1.1 Parameter Server The Parameter Server is used to store the model’s parameters. Each parameter server node is responsible for managing and updating one part of the model’s parameters, while each worker node only processes the subset of data corresponding to it.

1. Problems Facing Distributed Training Estimating training resources is difficult and cannot be automated How much compute, how much time, how much bandwidth, how many CPUs, how much memory — without enough accumulated experience it is hard to estimate accurately. The result is over-requesting and over-allocation, causing enormous resource waste.

This post comes mainly from an internal sharing session, and is also a summary of some recent work. 1. The Common Failure Handling Process The figure above shows a typical operations exception handling process. Along the timeline, there are the following key points in time: Failure occurs Failure detected Failure