Intel is a fierce player and represents the first legitimate competitive threat that Nvidia has seen in the space. I believe, however, that Intel’s competitive position in this nascent field is overstated in the near- to medium-term and that expanding TAM and strong leadership from Nvidia’s team should ensure that the segment’s sales and profitability continue to grow, even if Intel gets a piece of the action.
It is apparent that NVIDIA’s new Tesla K20Xm GPU gives a huge performance improvement for real-world applications – up to 1.9x in this example (very close to the theoretical peak: 2x).
Nvidia today formally introduced its K20 top of the line family of GPUs. Tesla K20 series would consist of K20X and marginally slower K20.
The U.S. Department of Energy’s (DOE) Oak Ridge National Laboratory launched a new era of scientific supercomputing today with Titan, a system capable of churning through more than 20,000 trillion calculations each second-or 20 petaflop
This new version of Jacket brings even greater performance improvements through GPU computing for MATLAB codes. With v2.3, new support has been added for CUDA 5.0. This newer version of CUDA enables computation on the latest Kepler K20 GPUs of the NVIDIA Tesla product line.
In a recent blog post NVIDIA discussed the new Dynamic Parallelism feature of upcoming GPU Kepler K20 using Quicksort as an example. Dynamic Parallelism allows the GPU to operate more autonomously from the CPU by generating new work for itself at run-time, from inside a kernel.