Tesla Overview
The main difference between Fermi-based Tesla cards and the GeForce 500 series is the unlocked double-precision floating-point performance giving 1/2 of peak single-precision floating point performance in Tesla cards compared to 1/8 for GeForce cards. Additionally, the Tesla cards have ECC-protected memory and are available in models with higher on-board memory (up to 6GB).
Because of their very high computational power (measured in floating point operations per second or FLOPS) compared to previous microprocessors, the Tesla products target the high performance computing market. As of 2012, Nvidia Teslas power some of the world's fastest supercomputers, including Titan at Oak Ridge National Laboratory and Tianhe-1A, in Tianjin, China.
The lack of ability to output images to a display was the main difference between Tesla products and the consumer level GeForce cards and the professional level Quadro cards, but the latest Tesla C-class products include one Dual-Link DVI port. For equivalent single precision output, Fermi-based Nvidia GeForce cards have four times less dual-precision performance. Tesla products primarily operate:
- in simulations and in large scale calculations (especially floating-point calculations)
- for high-end image generation for applications in professional and scientific fields
- with the use of OpenCL or CUDA.
Nvidia intends to offer ARMv8 processor cores embedded into future Tesla GPUs as part of Project Denver. This will be a 64-bit follow on to the 32-bit Tegra chips.
Tesla itself will be followed by the TB/s Volta in 2016.
Read more about this topic: Nvidia Tesla
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