WebCal
Ctrl K

가이드

Multi-machine, multi-GPU parallel processing

가이드통합FAQ지원
가격블로그
빠른 시작Top-Up and BillingAccelerating Access to Academic ResourcesQuick StartIntroductionMaintenance and TroubleshootingNetwork
플랫폼JetBrain ProjectorTmpWebCal Scholars Program @2026Introduction to the Public Beta/Suqian Zone AAbout UsCopying Data Between InstancesAnalysis of Server Performance MetricsTidal Computing PowerLoad Balancing
중국산 칩Using Huawei MindIEHuawei Ascend NPUMooreThread GPU
환경 설정CUDA/cuDNNMinicondaPython3.XInstalling DependenciesOverviewImages
엔터프라이즈 기능Flexible DeploymentElastic Deployment Release NotesBest Practices for Elastic DeploymentPerformance Metrics Monitoring
컨테이너 인스턴스JupyterLabRemote SSH ConnectionSave the imageScaling ConfigurationMulti-machine, multi-GPU parallel processingDaemonOverviewChange the billing methodMigration Example (Same Region)Migration ExamplesRemote DesktopReset the system
GPU 선택GPU SelectionPerformance Testing
데이터Upload DataDownload DataPublic DataPublic Cloud Storage (Highly Recommended)Compression / DecompressionFile StorageLocal data diskOverview
모범 사례FileZillaGitGromacsHuggingFaceKataGoLinux BasicsMPIOpenCLPyCharm Remote DevelopmentR (RStudio) InstallationSSH TunnelTensorBoardRemote Development with VSCodeVisdomVulkanXShellOpen PortsWeChat MessagesPerformanceExpose multiple servicesMoney-Saving TipsComputation Precision IssuesSoftware Sources

컨테이너 인스턴스

Multi-machine, multi-GPU parallel processing

2026. 07. 30.51615회 조회

Given that GPUs other than the A100 and similar models lack IB network and NVLink hardware support, multi-machine parallel processing is less efficient than single-machine parallel processing; therefore, we no longer support enabling internal IP addresses for multi-machine, multi-card parallel processing

If your computing needs can be met with a single-machine, multi-GPU setup, we highly recommend this approach (multi-machine parallel computing incurs significant network overhead, and its parallel efficiency is far lower than that of a single-machine, multi-GPU setup).For multi-GPU on a single machine, simply rent multiple GPUs within the same instance. For instances that are already running, you can change the number of GPUs by shutting down the instance and then scaling up or down; see Scaling.

다음 글About Us
Compute Rental 문서가이드(으)로 돌아가기