Tapping high-performance computing for new business value
Many
people
associate
high-performance
computing
(HPC),
also
known
as
supercomputing,
with
far-reaching
government-funded
research
or
consortia-led
efforts
to
map
the
human
genome
or
to
pursue
the
latest
cancer
cure.
Many
people
associate
high-performance
computing
(HPC),
also
known
as
supercomputing,
with
far-reaching
government-funded
research
or
consortia-led
efforts
to
map
the
human
genome
or
to
pursue
the
latest
cancer
cure.
But
HPC
can
also
be
used
to
advance
more
traditional
business
outcomes
—
from
fraud
detection
and
intelligent
operations
to
digital
transformation.
The
challenge:
making
complex
compute-intensive
technology
accessible
for
mainstream
use.
As
companies
digitally
transform
and
steer
toward
becoming
data-driven
businesses,
there
is
a
need
for
increased
computing
horsepower
to
manage
and
extract
business
intelligence
and
drive
data-intensive
workloads
at
scale.
The
rise
of
artificial
intelligence
(AI),
machine
learning
(ML),
and
real-time
analytics
applications,
often
deployed
at
the
edge,
can
utilize
HPC
resources
to
unlock
insights
from
data
and
efficiently
run
increasingly
large
and
more
complex
models
and
simulations.
The
convergence
of
HPC
with
AI-based
analytics
is
impacting
nearly
every
industry
and
across
a
wide
range
of
applications,
including
space
exploration,
drug
discovery,
financial
modeling,
automotive
design,
and
systems
engineering.
“HPC
is
becoming
a
utility
in
our
lives
—
people
aren’t
thinking
about
what
it
takes
to
design
this
tire,
validate
a
chip
design,
parse
and
analyze
customer
preferences,
do
risk
management,
or
build
a
3D
structure
of
the
COVID-19
virus,”
notes
Max
Alt,
distinguished
technologist
and
director
of
Hybrid
HPC
at
HPE.
“HPC
is
everywhere,
but
you
don’t
think
about
it,
because
it’s
hidden
at
the
core.”
HPC’s
scalable
architecture
is
particularly
well
suited
for
AI
applications,
given
the
nature
of
computation
required
and
the
unpredictable
growth
of
data
associated
with
these
workflows.
HPC’s
use
of
graphics-processing-unit
(GPU)
parallel
processing
power
—
coupled
with
its
simultaneous
processing
of
compute,
storage,
interconnects,
and
software
—
raises
the
bar
on
AI
efficiencies.
At
the
same
time,
such
applications
and
workflows
can
operate
and
scale
more
readily.
Even
with
widespread
usage,
there
is
more
opportunity
to
leverage
HPC
for
better
and
faster
outcomes
and
insights.
HPC
architecture
—
typically
clusters
of
CPU
and
GPUs
working
in
parallel
and
connected
to
a
high-speed
network
and
data
storage
system
—
is
expensive,
requiring
a
significant
capital
investment.
HPC
workloads
are
typically
associated
with
vast
data
sets,
which
means
that
public
cloud
might
be
an
expensive
option
due
to
requirements
regarding
latency
and
performance
issues.
In
addition,
data
security
and
data
gravity
concerns
often
rule
out
public
cloud.
Another
major
barrier
to
more
widespread
deployment:
a
lack
of
in-house
specialized
expertise
and
talent.
HPC
infrastructure
is
far
more
complex
than
traditional
IT
infrastructure,
requiring
specialized
skills
for
managing,
scheduling,
and
monitoring
workloads.
“You
have
tightly
coupled
computing
with
HPC,
so
all
of
the
servers
need
to
be
well
synchronized
and
performing
operations
in
parallel
together,”
Alt
explains.
“With
HPC,
everything
needs
to
be
in
sync,
and
if
one
node
goes
down,
it
can
fail
a
large,
expensive
job.
So,
you
need
to
make
sure
there
is
support
for
fault
tolerance.”
HPE
GreenLake
for
HPC
Is
a
Game
Changer
An
as-a-service
approach
can
address
many
of
these
challenges
and
unlock
the
power
of
HPC
for
digital
transformation.
HPE
GreenLake
for
HPC
enables
companies
to
unleash
the
power
of
HPC
without
having
to
make
big
up-front
investments
on
their
own.
This
as-a-service-based
delivery
model
enables
enterprises
to
pay
for
HPC
resources
based
on
the
capacity
they
use.
At
the
same
time,
it
provides
access
to
third-party
experts
who
can
manage
and
maintain
the
environment
in
a
company-owned
data
center
or
colocation
facility
while
freeing
up
internal
IT
departments.
“The
trend
of
consuming
what
used
to
be
a
boutique
computing
environment
now
as-a-service
is
growing
exponentially,”
Alt
says.
HPE
GreenLake
for
HPC
bundles
the
core
components
of
an
HPC
solution
(high-speed
storage,
parallel
file
systems,
low-latency
interconnect,
and
high-bandwidth
networking)
in
an
integrated
software
stack
that
can
be
assembled
to
meet
an
organization’s
specific
workload
needs.
As
part
of
the
HPE
GreenLake
edge-to-cloud
platform,
HPE
GreenLake
for
HPC
gives
organizations
access
to
turnkey
and
easily
scalable
HPC
capabilities
through
a
cloud
service
consumption
model
that’s
available
on-premises.
The
HPE
GreenLake
platform
experience
provides
transparency
for
HPC
usage
and
costs
and
delivers
self-service
capabilities;
users
pay
only
for
the
HPC
resources
they
consume,
and
built-in
buffer
capacity
allows
for
scalability,
including
unexpected
spikes
in
demand.
HPE
experts
also
manage
the
HPC
environment,
freeing
up
IT
resources
and
delivering
access
to
the
specialized
performance
tuning,
capacity
planning,
and
life
cycle
management
skills.
To
meet
the
needs
of
the
most
demanding
compute
and
data-intensive
workloads,
including
AI
and
ML
initiatives,
HPE
has
turbocharged
HPE
GreenLake
for
HPC
with
purpose-built
HPC
capabilities.
Among
the
more
notable
features
are
expanded
GPU
capabilities,
including
NVIDIA
Tensor
Core
models;
support
for
high-performance
HPE
Parallel
File
System
Storage;
multicloud
connector
APIs;
and
HPE
Slingshot,
a
high-performance
Ethernet
fabric
designed
to
meet
the
needs
of
data-intensive
AI
workloads.
HPE
also
released
lower
entry
points
to
HPC
to
make
the
capabilities
more
accessible
for
customers
looking
to
test
and
scale
workloads.
As
organizations
pursue
HPC
capabilities,
they
should
consider
the
following:
-
Stop
thinking
of
HPC
in
terms
of
a
specialized
boutique
technology; think
of
it
more
as a
common
utility
used
to
drive
business
outcomes.
-
Look
for
HPC
options
that
are
supported
by
a rich
ecosystem
of
complementary
tools
and
services to
drive
better
results
and
deliver
customer
excellence.
-
Evaluate the
HPE
GreenLake
for
HPC
model. Organizations
can
dial
capabilities
up
and
down,
depending
on
need,
while
simplifying
access
and
lowering
costs.
HPC
horsepower
is
critical,
as
data-intensive
workloads,
including
AI,
take
center
stage.
An
as-a-service
model
democratizes
what’s
traditionally
been
out
of
reach
for
most,
delivering
an
accessible
path
to
HPC
while
accelerating
data-first
business.
For
more
information,
visit https://www.hpe.com/us/en/hpe-greenlake-compute.html
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