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Course Outline

Introduction

  • Defining Kubefirst
  • Overview of Kubefirst features and architecture
  • Integration with open-source tools (Terraform, Vault, Argo, etc.)

Setting up the Development Environment

  • Installation and configuration of the Kubefirst SDK
  • Selection and setup of cloud platforms (Local, AWS, Civo, etc.)
  • Creating a Kubefirst project in Visual Studio Code
  • Exploration of project structure and files

Kubefirst Programming Model

  • Comprehending Kubefirst directives and clauses
  • Using parallel directives to create parallel regions
  • Applying kernel directives to parallelize kernels
  • Employing loop directives to parallelize loops

Kubefirst Data Management

  • Managing data movement via data directives
  • Synchronizing data using update directives
  • Enhancing data reuse through cache directives
  • Creating device functions with routine directives

Kubefirst API and Libraries

  • Understanding the Kubefirst API within host programs
  • Querying device information using the Kubefirst API
  • Configuring device number and type via the Kubefirst API
  • Managing errors and exceptions with the Kubefirst API
  • Utilizing Kubefirst libraries (math, random, complex)

Kubefirst Tools

  • Understanding the purpose of Kubefirst tools
  • Utilizing tools to profile and debug Kubefirst programs
  • Measuring and optimizing execution time with tools (PGI Compiler, NVIDIA Nsight Systems, Allinea Forge)

Kubefirst Applications

  • Best practices for development and deployment with Kubefirst
  • Interoperability with other programming models (CUDA, OpenCL, SYCL)
  • Integration with GPU libraries (cuBLAS, cuFFT)
  • Demonstration of the Kubefirst Metaphor demo application

Summary and Next Steps

Requirements

  • Foundational understanding of computer architecture and memory hierarchy
  • Working familiarity with Docker and Kubernetes concepts and commands

Target Audience

  • Developers
 14 Hours

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