While still shy of the theoretical 7В GHz limitation of GDDR5, this is well above the 4В GHz speed of the memory controller for Fermi. To accomplish this, Nvidia needed to design an entirely new memory controller and bus. The GPU can access any texture loaded into memory, increasing the number of available textures and removing the performance penalty of binding.ДЇinally, with Kepler, Nvidia was able to increase the memory clock to 6В GHz. With bindless textures, both limitations are removed. The second was that the CPU was doing unnecessary work: it had to load each texture, and also bind each texture loaded in memory to a slot in the binding table. This led to two limitations: one was that because the table was fixed in size, there could only be as many textures in use at one time as could fit in this table (128). Previously, textures needed to be bound by the CPU to a particular slot in a fixed-size table before the GPU could reference them. Kepler also introduced a new form of texture handling known as bindless textures. This is not only because the cores are more power efficient (two Kepler cores using about 90% of the power of one Fermi core, according to Nvidia's numbers), but also because the reduction in clock speed delivers a 50% reduction in power consumption in that area. By abandoning the shader clock found in their previous GPU designs, efficiency is increased, even though it requires more cores to achieve similar levels of performance. The primary way Nvidia achieved this goal was through the use of a unified clock. Where the goal of the previous architecture, Fermi, was to increase raw performance (particularly for compute and tessellation), Nvidia's goal with the Kepler architecture was to increase performance per watt, while still striving for overall performance increases. 2.1 Streaming Multiprocessor Architecture (SMX).

Nvidia gtx 680 vs 670 cuda cores