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Posted by Jonathan Allen on Jul 25, 2007 12:01 PM
Microsoft Research's Accelerator Project exposes a .NET library for performing parallel data processing using a computer's GPU.
Accelerator is a .NET 2.0 DLL that requires DirectX 9, included with Windows XP SP2, and a graphics card that supports Pixel Shader 2.0 or above. Graphics cards without hardware vertex processing, common on cheaper laptops, do not appear to work.
Accelerator is released under a non-commercial Shared Source license agreement. This means that while a developer can look at the source code, special permission is needed to actually use it in a production environment. Also, the source is not actually included in the installer or on the project's wiki page.
The current build can be downloaded from Microsoft Research. Note that the date on this page is incorrect. The build you get was actually uploaded in July of this year.
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Thin client paradigm characterized by web applications is a kludge that needs to be repudiated. Old compromises are no longer needed and it's time to move the presentation tier to where it belongs.
In this presentation filmed during QCon 2007, Jeff Sutherland, the creator of Scrum, talks about his visit at Google to do an analysis of Google's first implementation of Scrum.
In this article, Bryon Jacob and Chris Berry introduce AtomServer, their implementation of a full-fledged Atom Store based on Apache Abdera, which is now available as open source.
It is easy to think that virtualization applies only to servers. In reality the recent resurgence of the concept is also being applied to networking, storage, and application infrastructure.
In this article, Stefan Tilkov explains some of the most common anti-patterns found in applications that claim to follow a "RESTful" design and suggests ways to avoid them.
In this article, Adrien Louis and Marc Dutoo discuss the differences and relative merits of using orchestration vs. routing in a typical ESB setup, and discuss various implementation options.
Wayne Lund discusses batch processing, Spring Batch objectives and features, scenarios for usage, Spring Batch architecture, scaling, example code, failures and retrying, and the future roadmap.
Developer Jay Fields draws on his experiences as a ThoughtWorks consultant to describe effective user story estimation techniques.
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