 班級規模及環境--熱線:4008699035 手機:15921673576( 微信同號) |
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每期人數限3到5人。 |
| 上課時間和地點 |
開課地址：【上海】同濟大學(滬西)/新城金郡商務樓(11號線白銀路站)【深圳分部】：電影大廈(地鐵一號線大劇院站) 【武漢分部】：佳源大廈【成都分部】：領館區1號【沈陽分部】：沈陽理工大學【鄭州分部】：錦華大廈【石家莊分部】：瑞景大廈【北京分部】：北京中山學院 【南京分部】：金港大廈
最新開班 (連續班 、周末班、晚班）：2020年3月16日 |
| 實驗設備 |
☆資深工程師授課
☆注重質量
☆邊講邊練
☆合格學員免費推薦工作
★實驗設備請點擊這兒查看★ |
| 質量保障 |
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。 |
課程大綱 |
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- 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
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