LIQID Inc., one of the world's leading software companies delivering data center composability, announced
a new case study with
Durham University in Durham, England, describing its deployment of
Liqid composable disaggregated infrastructure (CDI) software. Durham
University is home to the COSmology MAchine (COSMA) operated by the
Institute for Computational Cosmology (ICC) and is a national
supercomputing facility that is part of the UK's Distributed Research
utilizing Advanced Computing (DiRAC) system. Liqid Matrix CDI software
is part of a system used to study the origins of the universe, composing
disaggregated GPUs in a tight footprint designed for a more sustainable
digital architecture. With the ability to grow as resources are needed,
the Liqid system will help researchers in the UK and around the world
unlock the mysteries of the 14 billion-year history of the cosmos with
far greater speed and efficiency than traditional data center systems.
"We
are honored to work with institutions like Durham University and COSMA
researchers to provide the resources to better explore the most profound
questions in science," said Sumit Puri, CEO & Cofounder, Liqid. "By
providing the kind of software-defined data performance and
architectural flexibility for powerful GPU, Liqid is enabling research
breakthroughs that would have been impossible with traditional, static
data center architectures so scientists can focus on results instead of
waiting for resources and performance to become available."
Liqid Matrix CDI Delivers Big Bang for Cosmologists with Adaptive, Efficient Architecture
"Durham
University is using cutting-edge CDI to accelerate research, improve
resource utilization, and reduce the university's carbon footprint,"
said Alistair Basden, technical manager for the DiRAC Memory Intensive
Service at Durham University, who was interviewed for the case study
entitled Durham University's Institute for Computational Cosmology Accelerates Results with Composability from Liqid.
The
COSMA memory-intensive system is designed specifically to support the
largest cosmological simulations, most notably running simulations
starting with the Big Bang and propagating through the entire history of
the universe. Each simulation of dark matter, dark energy, black holes,
galaxies and other structures in the universe often takes months to
run, followed by long periods of data analysis.
While
all of the applications deployed by DiRAC are memory intensive,
valuable GPU resources are required for some of its most challenging
simulations and analysis. Durham University chose Liqid Matrix
software-based composable system in order to be able to share and scale
GPUs in the exact amounts required for any given workload. Once the
workload has been completed, GPU resources can be redistributed through
Liqid Matrix software for use by other applications.
"It
would be wasteful for us to populate all our nodes with GPUs," Basden
said in an interview for the case study. "Instead, we have some fat
compute nodes and a login node, and we're able to move GPUs between
those systems. Composing our GPUs gives us flexibility with a smaller
number of GPUs. We can individually populate the servers with one or
more GPUs as required at the click of a button."
Durham
University IT is also deploying Liqid Matrix-based systems as an
element of its overall strategy for a more sustainable IT ecosystem.
Software-based composability enables users to do more with less,
increasing efficiency and curtailing the need for physical space to
store the hardware while providing significant reductions in cooling and
water requirements.
"Rather
than populating all our servers with GPUs, we can compose the resources
we need to each server. That reduces our carbon footprint," said
Basden.
To learn more about Liqid's academic deployments, review Liqid's case study outlining the company's work with the University of Illinois at Chicago's Electronic Visualization Laboratory.
Schedule an appointment with an expert on solutions based on Liqid
Matrix CDI software-based and set up a free infrastructure evaluation.