This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that manage their use beyond the most common consumer-grade GPU installations. They will learn how to manage asynchronous workflows, sending and receiving events to encapsulate data transfers and control signals. Also, students will walk through application of GPUs to sorting of data and processing images, implementing their own software using these techniques and libraries.
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GPU Programming 專項課程约翰霍普金斯大学課程信息
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第 3 門課程（共 4 門）
中級
Some experience in C/C++ programming
完成時間大約為29 小時
英語（English）
字幕：英語（English）
您將學到的內容有
Students will learn to develop software that can be run in computational environments that include multiple CPUs and GPUs.
Students will develop software that uses CUDA to create interactive GPU computational processing kernels for handling asynchronous data.
Students will use CUDA, hardware memory capabilities, and algorithms/libraries to solve programming challenges including image processing.
您將獲得的技能
- Cuda
- Algorithms
- C/C++
- GPU
- Nvidia
可靈活調整截止日期
根據您的日程表重置截止日期。
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 3 門課程（共 4 門）
中級
Some experience in C/C++ programming
完成時間大約為29 小時
英語（English）
字幕：英語（English）
提供方
约翰霍普金斯大学
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
授課大綱 - 您將從這門課程中學到什麼
完成時間為 4 小時
Course Overview
The purpose of this module is for students to understand how the course will be run, topics, how they will be assessed, and expectations.
完成時間為 4 小時
3 個視頻 （總計 11 分鐘）, 1 個閱讀材料, 1 個測驗
完成時間為 10 小時
Multiple CPU/GPU Systems
In professional settings, use of one CPU managing one GPU, is not a viable configuration to solve complex challenges. Students will apply CUDA capabilities for allowing multiple CPUs to communicate and manage software kernels on multiple GPUs. This will allow for scaling the size of input data and computational complexity. Students will learn the advantages and limitations of this form of synchronous processing.
完成時間為 10 小時
7 個視頻 （總計 32 分鐘）
完成時間為 4 小時
CUDA Events and Streams
Students will learn to utilize CUDA events and streams in their programs, to allow for asynchronous data and control flows. This will allow more interactive and long-lasting software, including analytic user interfaces, near live-streaming video or financial feeds, and dynamic business processing systems.
完成時間為 4 小時
5 個視頻 （總計 28 分鐘）, 2 個閱讀材料, 1 個測驗
完成時間為 5 小時
Sorting Using GPUs
The purpose of this module is for students to understand the basis in hardware and software that CUDA uses. This is required to appropriately develop software to optimally take advantage of GPU resources.
完成時間為 5 小時
11 個視頻 （總計 57 分鐘）, 1 個閱讀材料, 1 個測驗
關於 GPU Programming 專項課程
This specialization is intended for data scientists and software developers to create software that uses commonly available hardware. Students will be introduced to CUDA and libraries that allow for performing numerous computations in parallel and rapidly. Applications for these skills are machine learning, image/audio signal processing, and data processing.
常見問題
我什么时候能够访问课程视频和作业？
我订阅此专项课程后会得到什么？
有助学金吗？
Can I program on my own desktop/laptop
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