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2009 Interactive Data Visualization, Inc. NVIDIA nvidia GT 240 Driver been working closely with Microsoft on the development of Windows 10 and DirectX 12. Coinciding with the arrival of Windows 10, this Game Ready driver includes the latest tweaks, bug fixes, and optimizations to ensure you have the best possible gaming experience.
Please go to main driver page to find latest NVIDIA drivers. Please forward this error screen to 78.
Większość użytkowników wybiera tę wersję w celu uzyskania optymalnej stabilności i wydajności. Zapewnia ona również certyfikację ISV oraz długi okres wsparcia. Użytkownicy czasami wybierają tę wersję w celu uzyskania poprawek błędów, nowych funkcji, obsługi nowych zestawów nagłownych VR czy też nowych silników gier.
Your browser does not support iframes! 600 series GPUs in several PC games vs. 5 or earlier version of the CUDA Toolkit.
Nvidia’s goal with the Kepler architecture was to increase performance per watt, while still striving for overall performance increases. The primary way Nvidia achieved this goal was through the use of a unified clock.
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. Kepler also introduced a new form of texture handling known as bindless textures.
Previously, textures needed to be bound by the CPU to a particular slot in a fixed-size table before the GPU could reference them. 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.
With bindless textures, both limitations are removed. The GPU can access any texture loaded into memory, increasing the number of available textures and removing the performance penalty of binding. Finally, with Kepler, Nvidia was able to increase the memory clock to 6 GHz. To accomplish this, Nvidia needed to design an entirely new memory controller and bus.
While still shy of the theoretical 7 GHz limitation of GDDR5, this is well above the 4 GHz speed of the memory controller for Fermi. Kepler is named after the German mathematician, astronomer, and astrologer Johannes Kepler. The Kepler architecture employs a new Streaming Multiprocessor Architecture called SMX. The SMX are the key method for Kepler’s power efficiency as the whole GPU uses a single «Core Clock» rather than the double-pump «Shader Clock».
Consequently, the SMX needs additional processing units to execute a whole warp per cycle. Kepler also needed to increase raw GPU performance as to remain competitive. The GPU processing resources are also double. From 2 warp schedulers to 4 warp schedulers, 4 dispatch unit became 8 and the register file doubled to 64K entries as to increase performance.
With Kepler, Nvidia not only worked on power efficiency but also on area efficiency. Therefore, Nvidia opted to use eight dedicated FP64 CUDA cores in a SMX as to save die space, while still offering FP64 capabilities since all Kepler CUDA cores are not FP64 capable.
With the improvement Nvidia made on Kepler, the results include an increase in GPU graphic performance while downplaying FP64 performance. Additional die areas are acquired by replacing the complex hardware scheduler with a simple software scheduler. With software scheduling, warps scheduling was moved to Nvidia’s compiler and as the GPU math pipeline now has a fixed latency, it now include the utilization of instruction-level parallelism and superscalar execution in addition to thread-level parallelism.
As instructions are statically scheduled, scheduling inside a warp becomes redundant since the latency of the math pipeline is already known. This resulted an increase in die area space and power efficiency. GPU Boost is a new feature which is roughly analogous to turbo boosting of a CPU. The GPU is always guaranteed to run at a minimum clock speed, referred to as the «base clock».