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        1、培訓過程中，如有部分內容理解不透或消化不好，可免費在以后培訓班中重聽；
        2、培訓結束后,授課老師留給學員聯系方式,保障培訓效果,免費提供課后技術支持。
        3、培訓合格學員可享受免費推薦就業機會。

• Introduction
• Understanding the Fundamentals of Heterogeneous Computing Methodology
• Why Parallel Computing? Understanding the Need for Parallel Computing
• Multi-Core Processors - Architecture and Design
• Introduction to Threads, Thread Basics and Basic Concepts of Parallel Programming
• Understanding the Fundamentals of GPU Software Optimization Processes
• OpenMP - A Standard for Directive-Based Parallel Programming
• Hands on / Demonstration of Various Programs on Multicore Machines
• Introduction to GPU Computing
• GPUs for Parallel Computing
• GPUs Programming Model
• Hands on / Demonstration of Various Programs on GPU
• SDK, Toolkit and Installation of Environment for GPU
• Working with Various Libraries
• Demonstration of GPU and Tools with Sample Programs and OpenACC
• Understanding the CUDA Programming Model
• Learning the CUDA Architecture
• Exploring and Setting Up the CUDA Development Environments
• Working with the CUDA Runtime API
• Understanding the CUDA Memory Model
• Exploring Additional CUDA API Features
• Accessing Global Memory Efficiently in CUDA: Global Memory Optimization
• Optimizing Data Transfers in CUDA Using CUDA Streams
• Using Shared Memory in CUDA
• Understanding and Using Atomic Operations and Instructions in CUDA
• Case Study: Basic Digital Image Processing with CUDA
• Working with Multi-GPU Programming
• Advanced Hardware Profiling and Sampling on NVIDIA / CUDA
• Using CUDA Dynamic Parallelism API for Dynamic Kernel Launch
• Summary and Conclusion