WebCal
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Introduction

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クイックスタートTop-Up and BillingAccelerating Access to Academic ResourcesQuick StartIntroductionMaintenance and TroubleshootingNetwork
プラットフォームJetBrain ProjectorTmpWebCal Scholars Program @2026Introduction to the Public Beta/Suqian Zone AAbout UsCopying Data Between InstancesAnalysis of Server Performance MetricsTidal Computing PowerLoad Balancing
中国製チップUsing Huawei MindIEHuawei Ascend NPUMooreThread GPU
環境設定CUDA/cuDNNMinicondaPython3.XInstalling DependenciesOverviewImages
エンタープライズ機能Flexible DeploymentElastic Deployment Release NotesBest Practices for Elastic DeploymentPerformance Metrics Monitoring
コンテナインスタンスJupyterLabRemote SSH ConnectionSave the imageScaling ConfigurationMulti-machine, multi-GPU parallel processingDaemonOverviewChange the billing methodMigration Example (Same Region)Migration ExamplesRemote DesktopReset the system
GPU の選び方GPU SelectionPerformance Testing
データUpload DataDownload DataPublic DataPublic Cloud Storage (Highly Recommended)Compression / DecompressionFile StorageLocal data diskOverview
ベストプラクティスFileZillaGitGromacsHuggingFaceKataGoLinux BasicsMPIOpenCLPyCharm Remote DevelopmentR (RStudio) InstallationSSH TunnelTensorBoardRemote Development with VSCodeVisdomVulkanXShellOpen PortsWeChat MessagesPerformanceExpose multiple servicesMoney-Saving TipsComputation Precision IssuesSoftware Sources

クイックスタート

Introduction

2026/07/3034501の閲覧数

Important Notice: Cryptocurrency mining is strictly prohibited. Accounts will be suspended without exception upon detection.


👉 The goal of WebCal is to provide users with stable, reliable, and reasonably priced GPU computing power, ensuring that GPUs are no longer a roadblock on your path to becoming a data scientist.

👉Must-Read Documentation:

  1. Quick Start
  2. Instance Data Retention Guidelines
  3. Start the daemon

👉Frequently Used Documentation:

  1. How to Choose a GPU
  2. Upload Data
  3. Download Data
  4. Set Up Your Environment
  5. Public Cloud Storage (Highly Recommended)
  6. VSCode
  7. PyCharm
次の記事CUDA/cuDNN
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