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From YouTube: Scalable Locking
Description
Currently, Eclipse OpenJ9 uses OMR’s Test & Test & Set (TATAS) locks a.k.a. spinlocks with compare and swap (CAS) for synchronization, which are known to be unfair. TATAS locks collapse on massively parallel systems during high lock contention where many threads attempt to acquire a lock simultaneously. This talk will cover the following:
1) Does transitioning to scalable locks, such as the Mellor-Crummey & Scott (MCS) queue-based spinlock, in OpenJ9 resolve the TATAS bottleneck?2) Do features, such as lock cohorting, concurrency restriction, transactional lock elision (TLE) and scalable statistics counters, help further improve locking performance in OpenJ9?
B
A
high
concept
known
as
mechanical
sympathy,
which
refers
to
understanding
how
the
hardware
works
and
into
consideration
when
this,
the
software,
we
will
see
how
open
G
lines
current
locking
strategy
becomes
like
under
contention,
and
then
we
will
learn
how
the
current
design
goes
against
principle
of
mechanical
sympathy,
dive
into
scalable
locks
and
associated
features
girl.
It's
not
just
to
resolve
the
both
seen
in
open
j9
locking,
but
it
is
also
to
make
open,
g9,
locking,
more
scalable,
competitive
and
future
ready.
B
B
It's
going
to
focus
on
scalability
of
locks
to
evaluate
a
locks
scalability,
we
need
to
know
what
lock
contention
is
contention
is
evaluated
by
the
number
of
threads
that
are
competing
to
acquire
the
lock.
At
the
same
time,
the
lock
contention
would
refer
to
fewer
threads,
wanting
to
acquire
the
lock,
whereas
high
lock
contention
would
refer
to
a
substantially
larger
number
of
threads
then
want
to
acquire.
B
The
look,
please
refer
to
the
graph
on
the
slide
to
visualize
the
locks
performance,
which
is
on
the
y
axis
in
terms
of
time
to
acquire
a
lock
varies
with
the
lock
contention,
which
is
on
the
x
axis
and
represented
by
the
number
of
threads,
which
one
to
a
or
compete
for
the
look.
At
the
same
time,
g9
bottleneck,
which
will
become
a
later
arises
you
during
high-low
contention
and
the
two
main
symptoms
of
high
lock
contention,
are
a
drop
in
throughput
and
a
very
high
resource
utilization,
which
prevents
useful
work
from
being
done.
B
Language,
abstracts
locking
so
a
Java
developer
doesn't
need
to
worry
about
locking
in
the
Java
code.
The
Java
language
provides
a
synchronized
keyword
for
abstracting
looks
an
example.
Use
case
of
the
synchronized
keyword
has
been
provided.
The
Java
Virtual
Machine
is
responsible
for
supporting
the
cigarettes
keyword
and
implementing
the
locking
features.
An
example
of
high-low
contention
in
Java
would
be
where
hundred
threads
use,
the
synchronized
keyword
on
a
single
object
on
a
2015.
At
the
same
time,
we
dive
into
open
g9,
locking
bottleneck.
Let's
see
how
open
g9
implements,
locking
and.
B
You
know
uses
a
data
structure
named
system
monitors
for
locking
when
there
is
lock
contention.
This
data
structure
is
not
only
used
with
Java
objects,
but
it
is
also
used
by
the
VM
jet
and
GC
native
threads.
This
data
structure
is
maintained
in
our
mark.
It
implements
a
type
of
lock
which
performs
good
at
low,
lock
contention
but
collapses
at
high,
lock
contention
the
next.
We
will
study
the
types
lock
used
in
the
system
monitor
and
why
it
collapses
at
high,
lock
contention.
B
The
system
monitor
implements
testin
testin,
set
law
or
tates,
look,
which
is
a
type
of
lock
with
a
global,
lock
state
focal
key
word
here
is
global.
Global
Hawk
state
is
shared
among
all
the
threads
that
want
to
acquire
the
lock.
We
will
see
how
this
global,
lock
state
becomes
the
bottleneck
before
diving
into
tates
lock.
We
will
study
the
performance
bottleneck
in
the
context
of
the
test
and
set
or
Tata
start
as
lock,
which
is
a
simpler
form
of
the
TARDIS.
Look
simple
implementation
of
the
task.
B
Let's
rely
upon
a
computer
and
swap
operation
cask
operation
in
order
to
update
the
global
log
state,
and
then
this
pin
indefinitely
performing
the
cache
until
they
can
acquire
the
lock.
In
practice
we
won't
spin
indefinitely.
We
use
a
technique
known
as
spin
and
then
park
the
threads
only
spin
for
a
short
period
of
time
and
then
park
themselves
apart.
Technique
allows
threads
to
perform
useful
work.
B
You
guys
can
see
the
me
OSI
protocol,
which
is
used
on
most
modern
architectures.
In
this
protocol,
a
cache
line
can
exist
in
either
of
the
five
listed
States
modified,
earned
exclusive
and
invalid.
How
does
a
caste
operation
impact
the
processors
caches
performance
of
an
uncontained
uncontained
cache,
which
would
translate
to
one
thread
trying
to
acquire
the
look?
The
global,
lock
state
would
persist
in
one
cache
in
an
exclusive
state
which
is
going
to
be
very
cheap
to
maintain
as
the
Lord
becomes
contended
different
threads
would
perform
cars
on
the
global
log
state.
B
This
would
lead
to
a
lot
of
cache
invalidations
and
maybe
bus
traffic
Emily
Caen
did
it
heavily
contended.
Kaz
operations
can
saturate
the
processors
caches
and
buses.
The
locking
code
will
prevent
other
useful
work
to
be
performed
due
to
the
hardware.
Saturation
would
be
a
scalability
killer
for
a
nation
which
wants
to
scale
by
increasing
the
number
of
threads,
so
we
just
covered
has
operation,
but
on
other
architectures
such
as
PPC.
B
Everyone
should
know
that
l1
cache
is
smaller
and
faster
and
closer
to
the
curve.
L2
cache
is
bigger
than
the
l1
cache
and
further
away
from
the
curve.
In
this
example,
it's
1
&
3
are
scheduled
on
curve
1
and
threads
2
min
for
our
schedules
on
core
to
read.
One
wants
to
acquire
the
lock
right,
one
will
get
the
lock
locks
global
state
from
the
main
memory
through
the
l2
cache
and
then
the
1
cache,
and,
let's
assume
no
one
owns
to
look
at
this
point
so
thread
1
will
successfully
acquire
to
look.
B
It's
only
thread,
one
competes
all
to
lock.
The
global
state
will
persist
in
one
set
of
caches
in
an
exclusive
state
which
is
going
to
be
inexpensive
to
maintain
third,
one
still
owns
to
look
now.
Our
thread
2
also
wants
to
acquire.
The
lock
will
execute
the
cast
operation
in
an
infinite
loop
until
it
acquires
the
look.
This
is
going
to
be
the
acquire
function
we
saw
a
few
slides
ago.
Every
catch
that
thread
2
performs
will
cause
bus
traffic
and
cache
invalidations.
This
is
not
useful
work.
B
B
Let's
kill
the
previous
example
and
consider
a
multi-core
processor
with
96
curves,
so,
instead
of
only
to
incur
to
competing
for
the
book,
let's
assume
a
thread
running
on
each
girl
wants
to
acquire
the
lock.
The
locks
global
state
would
need
to
be
maintained
in
all
the
ninety-six
cache
sets
in
the
processor.
B
It's
going
to
be
very
expensive.
You're
wasting
resources
on
a
super
expensive
processor.
Just
for
acquiring
your
log
work
is
being
done
via
plaque.
The
applications
performance
is
going
to
be
drastically
impacted,
most
likely
it
will
experience
a
scalability
collapse
again.
I
would
like
to
remind
everyone
about
mechanical
sympathy
at
this
point
know
your
hardware,
when
you
design
your
software
neglecting
this
basic
principle
would
lead
to
you.
Failure
at
some
point.
B
B
Engineering
system
monitors,
use,
testin,
testin,
set
or
status
looks
the
difference
between
tabs
and
TARDIS
locks
is
reflected
in
the
acquire
function
which
is
shown
on
the
left
side
of
this
light
in
the
acquire
operation
for
the
TARDIS
look.
There
is
an
additional
while
loop,
which
did
not
exist
in
the
tab
this,
while
loop
acts
as
a
as
a
buffer
for
the
Cavs
operation
supposed
to
reduce
the
frequency
of
Cavs
operations.
B
See
the
performance
of
eight
has
tartars
and
an
ID
lock
has
an
tartars
behaves.
Similarly,
the
difference
is
in
the
point
of
collapse.
The
TARDIS
look
scales
little
better
than
the
task
log.
Before
reaching
its
inevitable
collapse.
The
slight
improvement
in
the
TARDIS
performance
is
DDD
reduction
in
the
castle.
Creation
has
operations
which
resulted
from
the
additional
while
loop.
We
saw
in
the
previous
light.
B
B
Well,
variants
of
Cubase
looks
here:
I
have
listed
7
variants
of
Cubase
locks,
keyless
lock,
sir,
had
highly
valued
for
their
performance
benefits
on
modern
processor
architectures.
It
has,
it
has
been
ordered
adopted
by
IBM
and
some
of
its
products.
Even
the
Linux
kernel
has
started
using
Cubase
locks
since
the
past
5
years
gone.
As
far
as
to
item
k42
looks
the
amazing
value,
Cubase
lakhs
per
wipe.
B
B
B
It
also
contains
a
pointer
to
the
next
element
in
the
queue
to
the
next
threads
note
that
required.
Lock.
You
add
elements
to
the
key.
The
atomic
exchange
operation
is
used
generally
asked
at.
This
point
is:
what's
the
difference
between
an
atomic
exchange
and
a
compare
and
swap
operation
right
to
a
memory
address
atomically
a
scan
fail
if
the
computer
doesn't
succeed,
so
it
has
to
be
repeated
until
it
is
successful,
whereas
an
atomic
exchange
or
creation
of
a
succeeds.
This
should
summarize
the
main
difference
between
an
atomic
exchange
and
a
compare
and
swap
operation.
B
B
One
wants
to
acquire
the
look,
the
thread,
one,
a
pins,
it's
very
specific
nerd
to
the
queues
tail,
which
is
shown
as
thread
1
or
t1
on
the
slide
and
the
lock
now
points
to
the
thread
ones.
Queue
nerd,
t1
read
one
notices
that
there
is
no
one
in
the
queue
other
than
itself
and
it
ends
up
acquiring
to
look.
B
To
you
all
so,
once
you
acquire
the
Lochner,
but
thread,
1
still
means
to
look
red
to
will
append
and
a
limit
to
the
Q's
tail,
which
is
going
to
be
similar
to
what
thread
wondered.
Look
will
point
to
thread
to
Z.
You
note,
because
in
a
queue
elements
are
generally
appended
to
the
tail
of
the
queue
aqua
pointed
t2
to
will
notice
that
there
is
another
threads
node
in
the
queue.
B
So
it
will
update
Iman's
next
field
to
point
to
its
key
node
and
it
is
going
to
busy
wait
or
spin
until
its
local
state
is
updated
to
true
by
the
current
owner
current
LOC
owner
when
it
releases
the
lock
step
forward.
Let's
say
it's:
3
also
wants
to
acquire
the
lock.
It
will
perform
the
same
steps
as
thread
to
a
pen.
It's
known
to
the
tail
of
the
queue
and
lock.
We
will
point
to
the
tread
to
thread
three's,
nerd,
3,
even
loaders
thread.
2
is
already
in
the
queue
waiting
for
the
lock.
D
B
Case
where
a
thread
wants
to
release
the
lock
in
this
case
thread
1
releases,
the
lock,
while
releasing
the
lock
thread.
1,
will
update
the
local
state
in
thread
twos
node
to
true
which
is
waiting
to
acquire.
The
lock
will
note
the
change
in
the
local
state
from
false
to
true
and
then
acquire
the
lock.
Similarly
thread.
3
will
once
thread
2
releases,
the
lock
and,
at
the
end
the
queue
will
again
be
empty
until
other
threads
want
to
acquire
the
lock.
This
summarizes
the
basic
working
of
the
MCS
lock.
B
The
MCS
look
better
than
the
tightest
look
difference
is
in
how
the
lock
state
is
maintained.
In
the
tardis
talk,
there
is
a
global,
lock
state
which
is
shared
among
all
the
threads
in
the
MCS
lock.
Each
thread
has
its
own
specific,
lock
state,
which
only
gets
updated
by
one
thread,
which
is
going
to
be
the
next
limit
in
the
queue
each
thread
has
its
own
lock
state,
and
only
one
thread
is
ever
going
to
update
that
local,
lock
state.
B
B
Look
at
the
of
Tartus
in
mcs
locks.
This
light
has
the
acquire
functions
for
both
this
look
and
the
mcs
lock
artists
acquire
is
on
the
left
side
of
the
slide
and
the
mcs
acquire
is
on
the
right
side
of
the
slide.
In
the
TARDIS.
Lock
there
can
be
unbounded,
has
operations
violet
threads
pins,
you
acquire
the
lock
by
updating
the
locks
of
global
state,
but
in
the
MCS
look
here
is
note
as
needed,
while
spinning,
because
only
one
thread
will
update
our
threads
local
state,
so
you
don't
need
Tama
City.
B
B
The
performance
data
is
taken
from
a
locking
paper,
which
is
shown
at
the
bottom
of
the
slide.
It
was
collected
using
a
micro
benchmark,
mirror
threads
compete
for
a
critical
section,
wire
lock.
It
is
written
in
C
and
it
doesn't
reflect
performance
of
a
java
application.
The
benchmark
measure,
Steve,
lock
performance,
while
increasing
low
contention.
B
The
lock
performance
is
shown
on
the
y
axis
in
terms
of
throughput
of
look
acquires
per
second,
and
the
low
contention
is
shown
on
the
x
axis
in
terms
of
the
number
of
threads
that
want
assignment
Dainius
li
impede
for
the
lock.
The
blue
line
in
the
graph
shows
the
performance
of
the
tightest
lock
and
the
orange
line
shows
the
performance
of
the
MCS
lock.
B
B
B
Just
looking
at
trooper
won't
be
a
complete
evaluation
of
the
MCS
log.
We
also
need
to
compare
the
worst
case,
space
complexity
or
the
memory
requirements
between
the
MCS
and
TARDIS
logs.
This
is
a
global
box
taped,
so
the
space
complexity
is
proportional
to
the
number
of
locks
in
the
MCS.
Log
of
Q
is
used.
Each
thread
competing
the
lockup
ends
its
own
node
into
the
Q,
so
the
space
complexity
is
going
to
it's
going
to
be
proportional
to
the
number
of
locks
multiplied
by
the
number
of
competing
threads.
B
The
mcs
lock
the
space
complexity
depends
on
the
lock
in
tension
and
in
most
java
applications,
only
three
to
four
percent
of
our
highly
contended.
So
we
won't
hit
the
worst-case
space
complexity
for
every
mcs
lock
in
the
JVM.
This
is
definitely
going
to
be
an
increase
in
the
memory
requirement
when
transitioning
from
the
taught
us
to
MGS
lock,
but
for
the
performance
improvement
from
the
alias
lock.
B
B
What
is
the
current
state
of
the
MCS
lock
implementation
in
open
j9?
We
have
implemented
a
basic
MCS,
look
and
incorporated
it
with
the
system
monitor
within
our
implementation.
Addresses
these
special
cases,
such
as
out
of
order
lock,
acquires
and
releases
the
support
for
park,
wait
and
notify
features
which
to
be
implemented
in
the
context
of
the
MCS
law.
B
You
do
not
cover
these
special
cases,
so
we
may
not
see
performance
improvements
similar
to
the
Academy
graphs
or
performance
numbers
that
we
recently
saw.
Current
implementation
is
complete.
There
is
an
Omar
pull
request
open
the
MCS
implementation.
It
passes
all
the
Omar
and
open
j9
testing.
The
only
pending
task
is
performance
benchmarking.
B
After
benchmarking,
we
can
most
likely
merge
this
pull
request.
After
a
code
review,
we
plan
to
further
optimize
and
improve
the
performance
of
the
basic
MCS
look
dive
into
your
future
work.
Other
ways
through
which
we
can
improve
the
basic
MCS
log
implementation
or
in
case
MCS
logs,
do
not
as
well
as
tardis
locks
in
all
workloads.
B
B
Just
look
have
similar
performance
to
the
tardis
look
for
low
log
contention
in
the
current
open,
GL
and
implementation.
The
tardis
log
takes
two
atomic
operations,
one
in
the
acquire
function
and
the
other
in
the
release
function.
This
is
in
the
best
case
scenario
for
the
tardis
log.
Mc
locks
in
the
worst
case
scenario
will
only
perform
two
atomic
operations,
one
in
acquire
function
and
the
other
in
the
release
function,
so
I
speculate
that
the
MCS
and
TARDIS
locks
should
have
the
same
performance
in
low,
lock
contention.
B
So
this
growth
few
slides
ago,
I
brought
it
back
to
compare
the
performance
of
MCS
in
Tartus
locks
under
low,
lock
contention.
The
new
addition
here
is
the
green
circle
and
the
green
arrow,
which
points
the
low
door
contention
area.
This
graph
reiterates
that
the
MCS
lock
has
similar
performance
Toutatis
under
low
lock
contention.
B
B
Reactive
locking
algorithms
come
to
play
these
algorithms
were
introduced
in
an
academic
paper
which
is
shown
at
the
bottom
of
the
slide.
You
will
use
a
reactive
algorithms
to
address
the
pure
performance
of
the
MCS,
lock
in
low
lock
contention,
workloads,
reactive
algorithms,
do
reactive,
algorithms
will
split
the
system
monitor
code
part
into
to
a
simple
or
default
code.
Part
would
be
to
use
the
TARDIS
log
for
handling
the
lock
contention
workloads.
B
We
will
need
instrumentation
to
measure
the
low
contention
as
the
locking
T
becomes
high
enough
for
the
MCS
lock
to
performed
better
than
the
TARDIS
look
from
the
Trotters.
Look
to
you
and
MZ
lock
in
the
system.
Monitor
reactive
approach
is
going
to
be
the
fallback
solution.
In
case
my
assumption
of
MCS
looks
performance
in
low,
lock
contention.
Workloads
ends
up
being
fault.
B
B
And
this
issue,
we
need
to
look
at
the
working
of
the
mcs
lock-in.
The
mcs
lock
only
one
thread.
Only
the
next
thread
in
the
queue
is
able
to
acquire
the
lock,
which
is
in
contrast
to
the
TARDIS,
lock,
we're
we're
all
the
threads
can
simultaneously
compete
for
the
work.
The
one
thread
which
is
able
to
acquire
the
lock
may
be
preempted
resuming
such
a
proof.
Such
preempted
threads
can
result
into
an
expensive
contact
switch
which
can
negatively
impact
the
locks
performance.
This
is
a
simple
description
for
the
lock
greater
preemption
issue.
B
B
B
You
guys
would
need
to
know
about
two
terms
before
understanding
what
concurrency
restriction
is.
The
first
term
is
active
thread
set,
which
means
a
set
of
threads
which
are
allowed
to
compete
for
the
lock
and
then
the
second
term
is
passive
thread
set,
which
means
or
which
comprises
of
a
set
of
threads
that
are
not
allowed.
You
acquire
the
look
into
what
is
the
objective
of
concurrency
restriction?
The
objective
is
stated
on
this
slide.
B
B
B
Vice-Versa,
in
order
to
achieve
the
objective
of
the
concurrency
restriction
feature
which
we
saw
in
the
previous
slide
unfairness
achieve,
it
is
achieved
by
occasionally
shed
yielding
the
latest
thread
which
wants
to
acquire
the
lock
the
latest
or
the
newest.
Fed
will
incur
the
least
cost
from
a
scheduling
perspective.
Since
it's
already
running
on
the
processor,
it
won't
have
to
go
through
an
expensive
context,
switch.
B
How
do
we
disrupt
order
in
the
MCS
lock?
This
is
accomplished
by
moving
an
element
from
the
tail
of
the
passive
queue
which
is
going
to
represent
newer
or
latest
thread,
and
then
we
will
move
this
element
to
the
head
of
the
active
queue
when
we
do
this
move,
the
element
or
the
thread
which
is
going
to
be
moved,
will
end
up
owning
the
look.
B
The
way
we
make
this
decision
is
going
to
be
random,
we
rely
upon
randomness
to
inject
unfairness
in
the
MCS
lock
vise
concurrency
restriction
aims
to
reduce
the
involuntary
preemption
rates
by
inducing
unfairness
to
the
MCS
locks
admission
policy.
In
future,
the
basic
mcs
lock
implementation
will
incorporate
concurrency
restriction
in
some
form.
This
will
allow
us
to
handle
the
lock
where
the
preemption
issue,
by
inducing
on
fairness,.
B
We
can
see
the
performance
of
the
MCS
lock
with
and
without
concurrency
restriction,
concurrency
restriction
and
the
performance
data
are
both
taken
from
an
academic
paper
which
is
included
at
the
bottom
of
the
slide.
The
benchmark
used
is
a
stress,
latency,
benchmark
measures,
lock
performance,
while
varying
the
low
contention
similar
to
the
previous
graphs,
lock,
performances
on
the
y
axis
and
the
lock
contention
is
on
the
x
axis.
B
It
is
very
clear
that
the
MCS
lock
with
concurrency
restriction,
achieves
and
maintains
a
steady
state
trooper
at
high
look
low
contention
in
one
of
the
previous
graphs.
We
saw
the
same
scalability
collapse
that
we
noticed
with
the
talus
lock,
but
with
concurrency
restriction.
The
scalability
collapse
no
longer
exists.
B
B
B
Your
the
impact
of
concurrency
restriction
is
that
the
number
of
active
threads
reduces
from
32
to
5,
which
means
only
5
threads
needed,
maintain
maximum
occupancy
of
the
critical
section,
and
the
impact
on
the
hardware
is
that
CPU
utilization
reduces
by
a
factor
of
three
ash
usage
drops
by
98
percent,
which
is
reflected
by
the
fewer
l3
misses.
Overall,
the
low
performance
with
concurrency
restriction
increases
by
a
factor
of
16
Press
by
these
numbers
and
there
it
will
be
amazing
to
have
such
a
feature
in
open
j9.
B
B
B
Hardware
instructions
only
take
few
cycles,
whereas
using
a
software
it's
like,
whereas
using
a
software
lock,
may
take
hundreds
of
cycles
on
a
CPU.
The
transactions
can
yield
better
performance
in
a
software
lock.
Yell
II
aims
to
maximize
usage
of
Hardware
transactional
memory,
leads
to
a
mission
of
the
software
lock
to
rely
upon
the
hardware
more
and
more
and
use
the
software
look
as
much
as
possible.
B
B
B
You
know
that
hardware
transactions
won't
always
succeed
in
the
presence
of
memory
conflicts
transactions
will
fail
and
in
case
of
a
failure,
our
hard
transaction
would
need
to
be
repeated.
Our
transactional
memory
instructions
are
cheap,
so
we
can
run
them
multiple
times
to
evaluate
the
affinity
of
a
critical
section
with
Hardware
transactions.
B
Good
performance
cannot
be
chief
with
hybrid
transactions.
Then
we
can
fall
back
to
using
the
software
look.
This
is
the
simple
premise
behind
PL
e
I
would
like
to
show
you
guys
an
abstract,
ele
design.
It
is
taken
from
an
academic
paper
which
is
referred
at
the
bottom
of
the
slide.
There
are
two
primary
code
pots
code
pot
represents
the
software
lock
and
the
red
color
part
represents.
The
hardware
transaction
part
has
provisions
for
instrumentation.
B
B
B
The
tle
design
here
we
can
see
a
specific
use
case.
Their
transactional
log
elision
yields
better
performance.
The
performance
data
from
the
same
academic
paper
attract
ele
design,
is
taken.
The
micro
benchmark
uses
a
skip
list
base
set,
which
is
a
data
structure
implemented
using
linked
lists.
It
is
designed
for
file
searches
mostly
performs,
insert
and
remove
operations
on
this
data
structure.
The
performance
graph
shows
the
logs
performance
on
the
y-axis
and
the
contention
on
the
x-axis.
B
B
Do
we
deduce
from
what
can
be
deduced
from
this
graph?
The
graph
shows
that
tle
performs
you
do
four
times
faster
than
just
using
a
softer
look,
clearly
improvement.
Ele
improvements
are
coming
from
the
hardware
transactions
yearly,
has
the
potential
to
further
improve
open,
G
and
I'm,
locking
if
it
is
implemented
effectively
within
open
Jana,
we
began
the
work
on
incorporating
Hydra
transactional
memory
into
open
genomes,
locking
strategy.
B
B
At
this
point,
we
are
very
close
to
the
end
of
the
presentation.
We
covered
a
lot
of
topics.
Today
we
saw
a
bottleneck
in
OpenGL,
locking
on
to
the
system.
One
usage
of
Tartus,
which
utilizes
a
global,
lock
state
leads
to
collapse.
Then
we
covered
MCS
a
cubed
and
how
it
can
help
with
the
throughput
collapse,
which
is
seen
with
the
hottest
look.
B
We
will
rely
upon
reactive
algorithms,
then
we
come
in
currency
restriction
and
how
it
solves
the
lot
greater
preemption
issue
by
inducing
unfairness
in
the
admission
policy,
and
we
talked
about
transactional,
look
lesion,
which
combines
hybrid
transactional
memory
and
software
lock
achieving
better
lock
of
performance.
This
dog
heavy
focus
on
the
basic
principle
of
mechanical
sympathy.
You
can
deserve
better
software.
If
you
are
aware,
the
line
Hardware
behaves
before
concluding
I
would
like
to
encourage
everyone
to
employ
the
concept
mechanicals
beti.
Whenever
you
write
or
design.
B
At
the
end
of
my
presentation,
but
before
I
would
just
the
help
that
I
received
from
that
Vijay
and
Shelley
in
for
this
presentation,
sincere
effort
in
improving
the
flow
and
organization
of
this
presentation
also
provided
a
lot
of
constructive
feedback.
The
right
dry
runs
I'm,
sincerely
grateful
for
their
hope
I.
Would
you
address
any
questions
if.
A
A
C
C
B
B
C
C
B
C
D
C
B
C
A
C
C
D
C
C
C
Is
a
contention:
how
are
you
going
to
avoid
out
order
thing?
You,
basically
the
the
the
reason
the
guy
going
to
release
it
is
checking.
It
is
node
whether
the
the
the
thing
is
now
the
node
is
containing
now
versus
the
thread
going
to
enter
is
going
to
write
to
that
thing
as
a
threat,
three
of
a
to
the
the
store
versus
that
reader
to
check
you
have
a
order
there.
You
have
a
how
to
synchronize
it
you,
you
have
a
problem
there
right
there.
D
C
B
C
Exactly
the
point
I
try
to
raise,
you
have
wasting
memory
location.
You
have
multiple
rather
going
to
either
modify
or
check.
You
are
going
to
check
it
yourself
or
there
are
other
other
threat
and
may
start
into
it.
Now
you
have
an
order
there,
whether
when
you
are
going
to
see
my
store
versus
how
I'm
going
to
wait
help
you
have
a
problem
to
piece
out
there.
C
C
C
C
C
C
C
A
Okay,
so
that
concludes
the
Vitaly
talks.
Today,
I
wanted
to
thank
Shelley
Lambert
for
organizing
the
events
in
Ottawa
who
currently,
as
the
Toronto
event
in
the
future,
I
look
forward
to
working
with
dalawa
team
more
in
terms
of
dreams.
Some
of
the
technologies
in
the
j9
be
m
and
G
C
teams
to
to
the
talk
series
so
that
the
team
can
also
benefit
from
the
salaat
knowledge
over
there.
Okay,
so
thank
you
old.