Nvidia is rolling out its Tesla GPU Preconfigured Cluster, an off-the-shelf, ready-to-deploy IT infrastructure system that will provide an option for researchers and engineers who are finding it difficult to get time on a supercomputer. The Nvidia Tesla cluster includes a mix of GPU-based systems and x86 CPU servers. Because GPUs use less energy than CPUs, using the Nvidia cluster means both access to computing capacity and reduced power consumption, Nvidia officials say.
is looking to make it easier for researchers and IT administrators to
add computing capability to their data centers while keeping down energy
Nvidia and about 20 of its partners May 4 launched the Tesla GPU
Preconfigured Cluster, an off-the-shelf system that Nvidia officials said
provides up to 30 times more performance than CPU-only solutions.
Additionally, GPU systems consume less power and are smaller and denser than
CPU-only systems. The result is that researchers and IT administrators, using
the Tesla GPU Preconfigured Cluster, can still offer the compute power needed
for HPC (high-performance computing)
workloads such as fluid dynamics, seismic processing and financial computing,
but at lower costs than CPU-only solutions.
The move is the latest by Nvidia
to bring its graphics technology into the supercomputing and HPC
which traditionally are powered by CPUs. According to Nvidia, systems running
on GPUs can offer users the computing capabilities they need at a price they
The Tesla GPU Preconfigured Cluster comes with x86 CPU servers combined with
Tesla S1070 1U (1.75-inch) GPU systems. Configurations start at 16 teraflops of
performance from four Tesla S1070s, with each system holding four Tesla 10-series
GPUs. Each system includes host servers, InfiniBand switches and cabling. They
also can be customized to suit the user's needs.
Nvidia officials said there is a growing need for accessible computing
offerings in the HPC space, where time on a
supercomputer can be difficult to get and buying traditional supercomputers is
"There are 15 [million] to 20 million engineers, scientists and
researchers around the world struggling for time on supercomputers, which has
led to a huge pent-up demand for computation," Andy Keane, general manager
of Nvidia's Tesla business, said in a statement.
Nvidia's new offering can bring many of these researchers an easy-to-deploy
GPU-powered supercomputing cluster that can do the work while reducing power
consumption, Keane said.
Nvidia's partners include Appro International, Cray, HPC
Technologies, Megaware, Microway and Penguin Computing.