A team of researchers has published a paper detailing the development of a new plasma physics platform for supercomputers, making it the first such platform to be built for this type of computing task.
The platform, called Plasma Physics, is based on the same architecture used in supercomputing, and has been built to run on the latest Intel Xeon E5 processors.
In addition to being built using the Intel Xeon processors, the platform runs on an NVIDIA Tesla P100 GPU, a new architecture that has been made available in a number of server and embedded processors.
This is a great thing, because it makes the system a lot easier to use and maintain.
This makes it more competitive than other platforms out there, because supercomputers use the GPU to render data.
That means they can run a lot faster and more efficiently than their predecessors.
It also makes it easier to scale and scale up, since supercomuters are able to run more data per second and more concurrently than their rivals.
It’s a good thing because it’s the most common type of compute architecture.
The team behind the project is called the Supercomputing Research Consortium (SRC).
The name is taken from the SRC, the scientific research organization that works on supercomputed applications in computing.
The project, led by Dr. Huiqing Zhao, a former IBM engineer, and Dr. Lianli Xu, a professor of physics at the University of Toronto, is part of a larger effort to develop and scale supercomposition technology.
The SRC has also announced the release of its first supercomposite project, which is based at the university’s Centre for Computing Systems.
The Supercomputers of the Future Supercomputer hardware is based around an Intel Xeon CPU.
But the Src team is not the only one building the platform.
NVIDIA has been building a new GPU for supercomputer-based computations for some time.
But its SuperComputers of tomorrow (SOCO) project is the first to combine a GPU and supercomputer.
This means it will run on a chip that has all of the same power, bandwidth, and processing power as an Intel Atom, and it will also run at up to 16TB of memory.
That’s a lot of memory, but not much more.
But there is more to supercompletions than just the CPU and GPU.
The technology also has to be scalable, meaning it has to scale up and down to handle the demand for data that it needs to process.
Supercompletion is also about reducing the amount of work required to compute a task.
And that is what the SNC is trying to do by combining a GPU with supercomposing, or merging together different GPUs into a single chip.
SuperComputing is still very much in its infancy, and the SREC is not planning to build a fully functioning system in the next year or two.
The research was published in the journal Physical Review Letters.