Vectorization Advisor Can Make Your Code Faster
Rick
Leinecker shows you how Vectorization Advisor easily works with
straightforward content, or helps identify issues such as dependencies,
so that you can develop reports,
analyses, and make adjustments that optimize your code. Find out more
and let us know what you think in the comments section on our story
page.
Learn More >>
2015年9月22日 星期二
2015年9月21日 星期一
軟體定義資料中心、混合雲和終端使用者運算
承如VMware執行長在第二天專題演講所提,未來的商業競爭是小博大、快勝慢的世界。從去年VMworld 2014完成三大願景的技術板塊:軟體定義資料中心、混合雲和終端使用者運算,
2015年9月18日 星期五
** 現在訂購! 享有 10% 的優惠折扣,優惠活動至 2015 年 9 月 30 日止! ** 舊版本升級至 RAD Studio 10 可讓您節省 45% 的費用! 買一送一優惠方案! 請立即行動!
** 現在訂購! 享有 10% 的優惠折扣,優惠活動至 2015 年 9 月 30 日止! **
舊版本升級至 RAD Studio 10 可讓您節省 45% 的費用!
買一送一優惠方案!
請立即行動!
舊版本升級至 RAD Studio 10 可讓您節省 45% 的費用!
買一送一優惠方案!
請立即行動!
2015年9月15日 星期二
Solve More Problems on the Same Machine
Solve More Problems on the Same Machine
Get the new data analytics tools for faster results.
Create faster code—faster.
Get the new data analytics tools for faster results.
Create faster code—faster.
Why Big Data Needs Parallelism
Why Big Data Needs Parallelism
Big Data is defined as data sets that are so large or complex that they don't fit into memory and traditional data processing applications struggles to deal with them. David Bolton explains how without parallelism, Big Data would be a lot harder to achieve. Find out more and tell us what you think in the comments section on our story page.
Big Data is defined as data sets that are so large or complex that they don't fit into memory and traditional data processing applications struggles to deal with them. David Bolton explains how without parallelism, Big Data would be a lot harder to achieve. Find out more and tell us what you think in the comments section on our story page.
2015年9月1日 星期二
以下 RAD Studio 10 精彩功能,是每一位程式設計師希望能立即上手的...
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Must-Read Guide to Parallel Programming and Optimization
Must-Read Guide to Parallel Programming and Optimization
Writing a print book about any parallel computing topic is daunting for several reasons, including the difficulty of covering the enormous amount of information in such a way that it fits into a book, yet has enough depth to provide usable information. But Rick Leinecker reviews a book that does just that. Take a look and let us know what you think in the comments section on our story page.
Writing a print book about any parallel computing topic is daunting for several reasons, including the difficulty of covering the enormous amount of information in such a way that it fits into a book, yet has enough depth to provide usable information. But Rick Leinecker reviews a book that does just that. Take a look and let us know what you think in the comments section on our story page.
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