GPUs can be used for much more than graphics processing. As opposed to a CPU, which can only run four or five threads at once, a GPU is made up of hundreds or even thousands of individual, low-powered cores, allowing it to perform thousands of concurrent operations. Because of this, GPUs can tackle large, complex problems on a much shorter time scale than CPUs. Dive into parallel programming on NVIDIA hardware with CUDA Succinctly by Chris Rose, and learn the basics of unlocking your graphics card.
Book Description
Topics included: Introduction • Creating a CUDA Project • Architecture • First Kernels • Porting from C++ • Shared Memory • Blocking with Shared Memory • NVIDIA Visual Profiler (NVVP) • Nsight • CUDA Libraries.
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Author(s): Chris Rose
Publisher: Syncfusion Inc.
Published: January 2015
Format(s): PDF, Mobi(Kindle)
File size: 3.13 MB
Number of pages: 119
Download / View Link(s): PDF, Mobi
Publisher: Syncfusion Inc.
Published: January 2015
Format(s): PDF, Mobi(Kindle)
File size: 3.13 MB
Number of pages: 119
Download / View Link(s): PDF, Mobi