GeForce 200 series

The GeForce 200 Series is the 10th generation of Nvidia's GeForce graphics processing units, still based on the Tesla (microarchitecture) (GT-codenamed chips), named after the inventor and physicist Nikola Tesla.

Architecture

The GeForce 200 Series introduces Nvidia's second generation of Tesla (microarchitecture), Nvidia's unified shader architecture; the first major update to it since introduced with the GeForce 8 Series.

The GeForce GTX 280 and GTX 260 are based on the same processor core. During the manufacturing process, GTX chips are binned and separated through defect testing of the core's logic functionality. Those that fail to meet the GTX 280 hardware specification are re-tested and binned as GTX 260 (which is specified with fewer stream processors, less ROPs and a narrower memory bus).

In late 2008, Nvidia re-released the GTX 260 with 216 stream processors, up from 192. Effectively, there were two GTX 260 cards in production with non-trivial performance differences.

GeForce

GeForce is a brand of graphics processing units (GPUs) designed by Nvidia. As of 2013, there have been twelve iterations of the design. The first GeForce products were discrete GPUs designed for add-on graphics boards, intended for the high-margin PC gaming market, and later diversification of the product line covered all tiers of the PC graphics market, ranging from cost-sensitive GPUs integrated on motherboards, to mainstream add-in retail boards. Most recently, GeForce technology has been introduced into Nvidia's line of embedded application processors, designed for electronic handhelds and mobile handsets.

With respect to discrete GPUs, found in add-in graphics-boards, Nvidia's GeForce and AMD's Radeon GPUs are the only remaining competitors in the high-end market. Along with its nearest competitor, the AMD Radeon, the GeForce architecture is moving toward GPGPU (General Purpose-Graphics Processor Unit). GPGPU is expected to expand GPU functionality beyond the traditional rasterization of 3D graphics, to turn it into a high-performance computing device able to execute arbitrary programming code in the same way a CPU does, but with different strengths (highly parallel execution of straightforward calculations) and weaknesses (worse performance for complex decision-making code).