A
full
assessment
of
para-virtualization
is
important,
because
without
knowledge
about
the
various
overheads,
users
can
not
understand
whether
using
virtualization
is
a
good
idea
or
not.
In
this
paper
we
are
very
interested
in
assessing
the
overheads
of
running
various
benchmarks
on
bare-‐metal,
as
well
as
on
para-‐virtualization.
The
idea
is
to
see
what
the
overheads
of
para-‐
virtualization
are,
as
well
as
looking
at
the
overheads
of
turning
on
monitoring
and
logging.
The
knowledge
from
assessing
various
benchmarks
on
these
different
systems
will
help
a
range
of
users
understand
the
use
of
virtualization
systems.
In
this
paper
we
assess
the
overheads
of
using
Xen,
VMware,
KVM
and
Citrix,
see
Table
1.
These
different
virtualization
systems
are
used
extensively
by
cloud-‐users.
We
are
using
various
Netlib1
benchmarks,
which
have
been
developed
by
the
University
of
Tennessee
at
Knoxville
(UTK),
and
Oak
Ridge
National
Laboratory
(ORNL).
In
order
to
assess
these
virtualization
systems,
we
run
the
benchmarks
on
bare-‐metal,
then
on
the
para-‐virtualization,
and
finally
we
turn
on
monitoring
and
logging.
The
later
is
important
as
users
are
interested
in
Service
Level
Agreements
(SLAs)
used
by
the
Cloud
providers,
and
the
use
of
logging
is
a
means
of
assessing
the
services
bought
and
used
from
commercial
providers.
In
this
paper
we
assess
the
virtualization
systems
on
three
different
systems.
We
use
the
Thamesblue
supercomputer,
the
Hactar
cluster
and
IBM
JS20
blade
server
(see
Table
2),
which
are
all
servers
available
at
the
University
of
Reading.
A
functional
virtualization
system
is
multi-‐layered
and
is
driven
by
the
privileged
components.
Virtualization
systems
can
host
multiple
guest
operating
systems,
which
run
on
its
own
domain,
and
the
system
schedules
virtual
CPUs
and
memory
within
each
Virtual
Machines
(VM)
to
make
the
best
use
of
the
available
resources.
The
guest-‐operating
system
schedules
each
application
accordingly.
You
can
deploy
virtualization
as
full
virtualization
or
para-‐virtualization.
Full
virtualization
provides
a
total
abstraction
of
the
underlying
physical
system
and
creates
a
new
virtual
system,
where
the
guest
operating
systems
can
run.
No
modifications
are
needed
in
the
guest
OS
or
application,
e.g.
the
guest
OS
or
application
is
not
aware
of
the
virtualized
environment
and
runs
normally.
Para-‐virualization
requires
user
modification
of
the
guest
operating
systems,
which
runs
on
the
virtual
machines,
e.g.
these
guest
operating
systems
are
aware
that
they
are
running
on
a
virtual
machine,
and
provide
near-‐native
performance.
You
can
deploy
both
para-‐virtualization
and
full
virtualization
across
various
virtualized
systems.
Para-‐virtualization
is
an
OS-‐assisted
virtualization;
where
some
modifications
are
made
in
the
guest
operating
system
to
enable
better
performance.
In
this
kind
of
virtualization,
the
guest
operating
system
is
aware
of
the
fact
that
it
is
running
on
the
virtualized
hardware
and
not
on
the
bare
hardware.
In
para-‐virtualization,
the
device
drivers
in
the
guest
operating
system
coordinate
the
device
drivers
of
host
operating
system
and
reduce
the
performance
overheads.
The
use
of
para-‐virtualization
[0]
is
intended
to
avoid
the
bottleneck
associated
with
slow
hardware
interrupts
that
exist
when
full
virtualization
is
employed.
It
has
revealed
[0]
that
para-‐
virtualization
does
not
impose
significant
performance
overhead
in
high
performance
computing,
and
this
in
turn
this
has
implications
for
the
use
of
cloud
computing
for
hosting
HPC
applications.
The
“apparent”
improvement
in
virtualization
has
led
us
to
formulate
the
hypothesis
that
certain
classes
of
HPC
applications
should
be
able
to
execute
in
a
cloud
environment,
with
minimal
performance
degradation.
In
order
to
support
this
hypothesis,
first
it
is
necessary
to
define
exactly
what
is
meant
by
a
“class”
of
application,
and
secondly
it
will
be
necessary
to
observe
application
performance,
both
within
a
virtual
machine
and
when
executing
on
bare
hardware.
A
further
potential
complication
is
associated
with
the
need
for
Cloud
service
providers
to
support
Service
Level
Agreements
(SLA),
so
that
system
utilisation
can
be
audited
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