Date d'abonnement : 2016
Accelerated Computing: Libraries C/C++
Earned avr. 9, 2017 PDT
Fundamentals of Accelerated Computing with CUDA C/C++
Earned avr. 8, 2017 PDT
Accelerated Computing: CUDA C/C++
Earned avr. 7, 2017 PDT
Accelerated Computing: Python Getting Started
Earned mars 2, 2017 PST
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
Accelerate your C/C++ applications on the massively parallel NVIDIA GPUs using CUDA. This course is for anyone with some C/C++ experience who’s interested in accelerating the performance of their applications beyond the limits of CPU-only programming. In this course, you’ll learn how to: • Extend your C/C++ code with the CUDA programming model • Write and launch kernels that execute with massive parallelism on an NVIDIA GPU • Profile and optimize your accelerated programs Upon completion, you’ll be able to write massively parallel heterogeneous programs on powerful NVIDIA GPUs, and optimize their performance by utilizing NVVP.
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
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