Parallel Programming with Microsoft Visual C++: Design Patterns for Decomposition and Coordination on Multicore Architectures
โ Scribed by Colin Campbell, Ade Miller
- Publisher
- Microsoft Press
- Year
- 2011
- Tongue
- English
- Leaves
- 186
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Your CPU meter shows a problem. One core is running at 100 percent, but all the other cores are idle. Your application is CPU-bound, but you are using only a fraction of the computing power of your multicore system. Is there a way to get better performance? The answer, in a nutshell, is parallel programming. Where you once would have written the kind of sequential code that is familiar to all programmers, you now find that this no longer meets your performance goals. To use your system's CPU resources efficiently, you need to split your application into pieces that can run at the same time.
๐ SIMILAR VOLUMES
Your CPU meter shows a problem. One core is running at 100 percent, but all the other cores are idle. Your application is CPU-bound, but you are using only a fraction of the computing power of your multicore system. Is there a way to get better performance?The answer, in a nutshell, is parallel prog
Your CPU meter shows a problem. One core is running at 100 percent, but all the other cores are idle. Your application is CPU-bound, but you are using only a fraction of the computing power of your multicore system. Is there a way to get better performance?The answer, in a nutshell, is parallel prog
Your CPU meter shows a problem. One core is running at 100 percent, but all the other cores are idle. Your application is CPU-bound, but you are using only a fraction of the computing power of your multicore system. Is there a way to get better performance?The answer, in a nutshell, is parallel prog
This guide shows Visual C++ programmers how to effectively take advantage of the multicore capabilities of modern PCs using the Microsoft platform.
The CPU meter shows the problem. One core is running at 100 percent, but all the other cores are idle. Your application is CPU-bound, but you are using only a fraction of the computing power of your multicore system. What next? The answer, in a nutshell, is parallel programming. Where you once would