Nimbix speeds up big data analytics with supercomputing cloud

HPC is not just for oil and gas industries anymore.

Designed with a focus on handling the massive amounts of data that needs to be processed by the oil and gas industries as part of their exploration for new sources, the Nimbix HPC cloud continues to grow by adding even more powerful Nvidia Tesla and GRID GPUs.

While the Nimbix JARVICE platform was designed for the traditional uses of HPC such as Seismic Processing and Reverse-Time-Migration that are stalwarts of the exploration industry, the processing power is appropriate for many other uses. Some applications — such as pharmaceutical modeling and image rendering — have become commonplace in the HPC world, but it is the advent of big data analytics that is making supercomputing mainstream.

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Nvidia has had a great deal of success with its GPUs and GPU accelerators in the HPC world. The Tesla GPUs are available for server and workstation deployment for use in scientific calculations, and the GRID GPUs are designed as a virtualization solution. Both boards are based on the Nvidia Kepler GPU architecture, which Nvidia positions as the world’s fastest most efficient HPC architecture. The architecture is designed to allow applications to work seamlessly with CPU/GPU HPC infrastructures, in order to achieve the highest possible performance from both technologies.

A cloud-based HPC solution such as Nimbix takes away many of the hurdles a business would find in implementing supercomputing on site. There is no need to invest in the HPC hardware, which is the largest obstacle to trialing an HPC solution; and the Nimbix JARVICE platform requires minimal programming on the user end to allow customers to take full advantage of the cloud HPC backend.

With an architecture that was designed from the start to crunch numbers and analyze extremely large data sets, HPC can be a very effective tool for doing big data analytics. A cloud service such as Nimbix will allow customers who would never consider an investment in HPC to get a good feel for its capabilities. In many cases, it can provide  sufficient processing and resources to meet the potential HPC needs of their business.