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Learn how to program GPUs with C/C++. With millions of GPU compute enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing - Learn More

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Total Labs: 4
Total Lab Credits: 40
Total Time: 05 h:42 m
Badge Earned:
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Learn how to program GPUs with Python. With millions of GPU compute enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing - Learn More

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Total Labs: 2
Total Lab Credits: 30
Total Time: 01 h:48 m
Badge Earned:
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Learn how to program GPUs with Fortran. With millions of GPU compute enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing - Learn More

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Total Labs: 3
Total Lab Credits: 25
Total Time: 04 h:19 m
Badge Earned:
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Using MATLAB for GPU computing lets you accelerate your applications with GPUs more easily than by using C or Fortran. With the familiar MATLAB language you can take advantage of the CUDA GPU computing technology without having to learn the intricacies of GPU architectures or low-level GPU computing libraries.

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Total Labs: 1
Total Lab Credits: 10
Total Time: 00 h:53 m
Badge Earned:
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Learn how to program GPUs with Libraries in C/C++. With millions of GPU compute enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing - Learn More

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Total Labs: 3
Total Lab Credits: 40
Total Time: 04 h:09 m
Badge Earned:
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Learn how to program GPUs with CUDA C/C++. With millions of GPU compute enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing - Learn More

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Total Labs: 3
Total Lab Credits: 45
Total Time: 04 h:39 m
Badge Earned:
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OpenACC is an accelerator programming standard that enables scientific and technical Fortran, C and (increasingly) C++ programmers to easily take advantage of the power of heterogeneous CPU/accelerator systems. OpenACC allows programmers to use simple compiler directives to identify which areas of code to accelerate, without requiring modification to the underlying code itself. By identifying parallel code segments, OpenACC directives allow the compiler to do the detailed work of mapping the computation onto the accelerator.

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Total Labs: 4
Total Lab Credits: 40
Total Time: 05 h:27 m
Badge Earned:
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This quest guides you through an Introduction to Deep Learning tools for accelerating deep learning on NVIDIA GPUs.

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Total Labs: 5
Total Lab Credits: 60
Total Time: 07 h:05 m
Badge Earned:
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Join NVIDIA’s deep learning experts for a free online course. This introductory course is comprised of five instructor-led classes that include interactive lectures, hands-on exercises, and office hours with the instructors.

You’ll learn everything you need to design, train and integrate neural network-powered artificial intelligence into your applications with widely-used open source frameworks and NVIDIA software. During the hands-on exercises, you will use GPUs and deep learning software in the cloud. Visit NVIDIA Developer Website for more details.

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