AI and Accelerated Computing Propel Energy Efficiency Across Industries

Artificial
intelligence
(AI)
and
accelerated
computing
are
making
significant
strides
in
enhancing
energy
efficiency
across
multiple
industries,
according
to
a
report
by
Lisbon
Council
Research.
These
advancements
are
crucial
as
data
centers
are
projected
to
account
for
up
to
4%
of
global
energy
consumption
in
the
near
future.

Why
Accelerated
Computing
Is
Sustainable
Computing

Accelerated
computing
leverages
the
parallel
processing
capabilities
of
NVIDIA
GPUs,
allowing
more
work
to
be
completed
in
less
time
and
consuming
less
energy
compared
to
traditional
CPU-based
systems.
This
form
of
computing
is
increasingly
recognized
as
sustainable
computing.

The
benefits
are
amplified
when
AI
is
incorporated,
given
its
inherently
parallel
nature.
A
report
from
Lisbon
Council
Research
highlighted
that
AI
applications
such
as
machine
learning
and
deep
learning
perform
significantly
better
on
GPUs
than
on
CPUs,
driving
substantial
energy
savings.

User
Experiences
With
Accelerated
AI

Industries
worldwide
are
reporting
notable
energy-efficiency
gains
through
the
use
of
AI
and
accelerated
computing.
For
instance,
financial
services
firm
Murex
tested
NVIDIA’s
Grace
Hopper
Superchip,
achieving
a
4x
reduction
in
energy
consumption
and
a
7x
reduction
in
time
to
completion
compared
to
CPU-only
systems.

Similarly,
Taiwan-based
Wistron
utilized
NVIDIA
Omniverse
to
create
a
digital
twin
of
a
testing
room,
improving
its
energy
efficiency
by
up
to
10%.
This
translated
to
a
reduction
of
120,000
kWh
in
electricity
consumption
annually
and
a
decrease
in
carbon
emissions
by
60,000
kilograms.

Up
to
80%
Fewer
Carbon
Emissions

The
RAPIDS
Accelerator
for
Apache
Spark
has
demonstrated
the
potential
to
reduce
the
carbon
footprint
for
data
analytics
by
up
to
80%,
while
also
delivering
5x
average
speedups
and
4x
reductions
in
computing
costs.
Major
corporations
such
as
Adobe,
AT&T,
and
the
U.S.
Internal
Revenue
Service
are
among
those
utilizing
this
technology.

In
healthcare,
Insilico
Medicine
leveraged
NVIDIA-powered
AI
to
discover
a
drug
candidate
for
a
rare
respiratory
disease,
reaching
phase
2
clinical
trials
at
a
fraction
of
the
usual
cost
and
time.

Speeding
Science
With
Accelerated
AI

The
National
Energy
Research
Scientific
Computing
Center
(NERSC)
has
also
reported
significant
energy
efficiency
gains
with
NVIDIA
A100
Tensor
Core
GPUs.
Their
applications
saw
an
average
5x
increase
in
energy
efficiency,
with
weather
forecasting
applications
achieving
nearly
10x
improvements.

In
a
recent
ranking
of
the
world’s
most
energy-efficient
supercomputers,
NVIDIA-powered
systems
dominated
the
top
positions,
highlighting
the
substantial
energy
savings
achievable
through
accelerated
computing.

Underestimated
Energy
Savings

Despite
these
gains,
some
forecasts
only
consider
the
energy
consumed
during
the
training
of
AI
models,
overlooking
the
efficiency
benefits
during
the
deployment
phase.
A
study
by
the
Information
Technology
and
Innovation
Foundation
(ITIF)
debunked
these
projections,
emphasizing
the
significant
energy
savings
AI
can
deliver
post-training.

The
report
urges
policymakers
to
recognize
the
potential
of
AI
in
achieving
a
low-carbon
future
and
to
support
its
adoption
to
maximize
economic
and
societal
benefits.

AI
Supports
Sustainability
Efforts

AI’s
role
in
promoting
sustainability
is
further
supported
by
various
reports.
For
example,
AI
can
enhance
weather
modeling
accuracy,
improve
crop
yield
predictions,
and
aid
in
the
discovery
of
efficient
battery
materials.

Governments
are
encouraged
to
adopt
AI
tools
to
decarbonize
operations,
with
NVIDIA
collaborating
with
numerous
startups
to
address
climate
issues
and
developing
Earth-2,
an
AI
supercomputer
dedicated
to
climate
science.

Enhancing
Energy
Efficiency
Across
the
Stack

Since
its
inception,
NVIDIA
has
focused
on
improving
energy
efficiency
across
its
products.
Recent
innovations
include
the
NVIDIA
GB200
Grace
Blackwell
Superchip,
which
offers
25x
energy
efficiency
over
previous
generations
in
AI
inference,
and
the
BlueField-3
DPUs,
which
can
reduce
power
consumption
by
up
to
30%
by
offloading
data
center
functions
from
CPUs.

Moreover,
NVIDIA’s
liquid-cooling
technology,
under
development
with
a
grant
from
the
U.S.
Department
of
Energy,
promises
a
20%
efficiency
improvement
over
current
air-cooled
systems.

These
advancements
underscore
NVIDIA’s
commitment
to
driving
energy
efficiency
and
supporting
sustainable
computing
practices
across
various
sectors.

For
more
information,
visit
the

original
source.

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source:
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