I think you are mistaken.
The Tesla does not get attached to a regular GPU at all. (With or without a physical bridge)
It handles/helps with regular processor tasks, not just Graphics. I think you need to read up on what you are talking about.
Titan, the World fastest Super-computer, uses this exact processor to whoop-ass. NOT in graphics, but in computational-processing brute power.
It has very little to do with boosting an existing graphics card. You are very much mistaken. But, don't listen to me....
Read this.....
What is GPU Computing? GPU computing is the use of a GPU (graphics processing unit) together with a CPU to accelerate general-purpose scientific and engineering applications. Pioneered five years ago by NVIDIA, GPU computing has quickly become an industry standard, enjoyed by millions of users worldwide and adopted by virtually all computing vendors.
GPU computing offers unprecedented application performance by offloading compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU. From a user's perspective, applications simply run significantly faster.
CPU + GPU is a powerful combination because CPUs consist of a few cores optimized for serial processing, while GPUs consist of thousands of smaller, more efficient cores designed for parallel performance. Serial portions of the code run on the CPU while parallel portions run on the GPU.
Most customers can immediately enjoy the power of GPU computing by using any of the GPU-accelerated applications listed in our
catalog, which highlights over one hundred, industry-leading applications. For developers, GPU computing offers a
vast ecosystem of tools and libraries from major software vendors.
Run your GPU-accelerated code
faster Test Drive a Tesla K20 GPU Accelerator.
Learn More. History of GPU Computing Graphics chips started as fixed-function graphics processors but became increasingly programmable and computationally powerful, which led NVIDIA to introduce the first GPU. In the 1999-2000 timeframe, computer scientists and domain scientists from various fields started using GPUs to accelerate a range of scientific applications. This was the advent of the movement called
GPGPU, or General-Purpose computation on GPU.
While users achieved unprecedented performance (over 100x compared to CPUs in some cases),the challenge was that GPGPU required the use of graphics programming APIs like OpenGL and Cg to program the GPU. This limited accessibility to the tremendous capability of GPUs for science.
NVIDIA recognized the potential of bringing this performance for the larger scientific community, invested in making the GPU fully programmable, and offered seamless experience for developers with familiar languages like
C, C++, and
Fortran.
GPU computing momentum is growing faster than ever before. Today, some of the fastest supercomputers in the world rely on GPUs to advance scientific discoveries; 600 universities around the world teach parallel computing with NVIDIA GPUs; and hundreds of thousands of developers are actively using GPUs.
All NVIDIA GPUs—GeForce®, Quadro®, and Tesla®— support GPU computing and the
CUDA® parallel programming model. Developers have access to NVIDIA GPUs in virtually any platform of their choice, including the latest
Apple MacBook Pro. However, we recommend Tesla GPUs for workloads where data reliability and overall performance are critical. For more details, please see “
Why Choose Tesla.”
Tesla GPUs are designed from the ground-up to accelerate scientific and technical computing workloads. Based on innovative features in the “
Kepler architecture,” the latest Tesla GPUs offer 3x more performance compared to the previous architecture, more than one teraflops of double-precision floating point while dramatically advancing programmability and efficiency. Kepler is the world’s fastest and most efficient high performance computing (HPC) architecture.
"GPUs have evolved to the point where many real-world applications are easily implemented on them and run significantly faster than on multi-core systems. Future computing architectures will be hybrid systems with parallel-core GPUs working in tandem with multi-core CPUs.'
Professor Jack Dongarra Director of the Innovative Computing Laboratory
The University of Tennessee
Another......
"
NVIDIA Unveils World's Fastest, Most Efficient Accelerators, Powers World's No. 1 Supercomputer Monday, November 12, 2012
SC12 -- NVIDIA today unveiled the NVIDIA® Tesla® K20 family of GPU accelerators, the highest performance, most efficient accelerators ever built, and the technology powering Titan, the world's fastest supercomputer according to the
TOP500 list released this morning at the
SC12 supercomputing conference.
Armed with 18,688 NVIDIA Tesla K20X GPU accelerators, the
Titan supercomputer at Oak Ridge National Laboratory in Oak Ridge, Tenn. seized the No. 1 supercomputer ranking in the world from Lawrence Livermore National Laboratory's Sequoia system with a performance record of 17.59 petaflops as measured by the LINPACK benchmark.[SUP]
(1)[/SUP]
Tesla K20 - Performance, Energy-Efficiency Leadership
Based on the revolutionary NVIDIA
Kepler™ compute architecture, the new Tesla K20 family features the Tesla K20X accelerator, the flagship of NVIDIA's Tesla accelerated computing product line.
Providing the highest computing performance ever available in a single processor, the K20X provides tenfold application acceleration when paired with leading CPUs.[SUP]
(2)[/SUP] It surpasses all other processors on two common measures of computational performance -- 3.95 teraflops single-precision and 1.31 teraflops double-precision peak floating point performance.
The new family also includes the Tesla K20 accelerator, which provides 3.52 teraflops of single-precision and 1.17 teraflops of double-precision peak performance. Tesla K20X and K20 GPU accelerators representing more than 30 petaflops of performance have already been delivered in the last 30 days. This is equivalent to the computational performance of last year's 10 fastest supercomputers combined."
more......
NVIDIA Newsroom - Releases - NVIDIA Unveils World's Fastest, Most Efficient Accelerators, Powers World's No. 1 Supercomputer - NVIDIA Newsroom