John Nolan shows the state of hardware acceleration with GPUs and FPGAs, why it's hard to write efficient code for them, and why to favor polymorphism over if statements for performance.
In this IEEE article, authors Frank Feinbube, Peter Troger and Andreas Polze discuss two major hardware trends in the desktop parallel programming space, multi-core CPU architectures and Graphics Processing Units (GPUs). They also talk about the best practices for GPU code optimization like algorithm design, memory transfer, control flow, instructions and precision.
Mike Williams, co-creator of Erlang discusses the history of and influences on Erlang as well as languages and paradigms used at Ericsson for large scale development and embedded programming.
GPU.NET 2.0 supports Mono, enabling building and deploying computational intensive applications for Linux and Mac OS X along the already supported Windows.
WebCL brings parallelism support to the browser, enabling JavaScript developers to write data intensive web applications. Nokia has a prototype for Firefox while Samsung has one for WebKit browsers.
Moonlight has been enhanced to support GPU-accelerated video playback. Silverlight 5 will do the same, but with extra features.
Moonlight 4.0 Preview 1 includes all the Silverlight 3.0 API and a part of Silverlight 4.0 API. New features include: Out-of-Browser, GPU-accelerated graphics, 3D transformation, shaders, V4L2 video capture, H.264 and AAC, and better smooth streaming.
GPU.NET is a managed solution integrated with Visual Studio 2010 for .NET developers and aimed at creating calculation intensive applications for GPU.
Amazon has announced the availability of Cluster GPU instances for high performance applications starting with an instance of 2 NVidia Tesla GPUs and going up to a cluster of 128 or more instances, appealing to financial analysis, imaging, biology, simulation, and other domains.
Recently David Reveman added significant amounts of hardware rendering to Novel’s Moonlight. This puts it in the lead over Silverlight, offers only a limited amount of hardware rendering support.
InfoQ catches up with Gary Frost from AMD who unveiled an alpha release of Aparapi, an API that allows programmers to write logic in Java to be executed on a GPU. GPUs are the massively parallel hardware acceleration chips originally installed in PCs to boost graphics rendering performance but that are now pushed to other kinds of compute-intensive tasks that have nothing to do with graphics.
