h questions history, current state of the art, and open researc · 2008. 10. 8. · rs for pn,...

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Page 1: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Fas

t Rea

ctor

Sim

ulat

ion

His

tory

, cur

rent

sta

te o

f the

art

, and

ope

n re

sear

ch q

uest

ions

Page 2: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Sod

ium

coo

led

fast

rea

ctor

(S

FR

) Lo

op D

esig

n

~40

0C

~55

0C

Page 3: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Key

poi

nt o

f fas

t vs.

ther

mal

rea

ctor

s

T

herm

al r

eact

ors

(e.g

. LW

Rs)

–N

eutr

ons

mod

erat

ed to

ther

mal

ene

rgie

s (u

sual

ly u

sing

wat

er)

–H

ighe

r pr

obab

ility

of f

issi

on ->

rel

ativ

ely

low

U-2

35 e

nric

hmen

t (~3%

)

–A

lso

high

pro

babi

lity

of c

aptu

re b

y U

-238

->

bui

ldup

of t

rans

uran

ics

–A

ll ex

istin

g co

mm

erci

al re

acto

rs a

re L

WR

s–

Maj

or s

pent

fuel

bur

den

+ in

effic

ient

reso

urce

usa

ge

F

ast r

eact

ors

(e.g

. LM

FB

Rs)

–N

eutr

on m

oder

atio

n m

inim

ized

–Lo

wer

-pro

babi

lity

of fi

ssio

n ->

hig

her

enric

hmen

t nee

ded

–Lo

w p

roba

bilit

y of

cap

ture

and

abi

lity

to fi

ssio

n tr

ansu

rani

cs/b

reed

plu

toni

um–

Key

to c

losi

ng fu

el c

ycle

+ lo

ng-t

erm

res

ourc

e m

anag

emen

t–

Mos

t bui

lt to

dat

e ha

ve b

een

rese

arch

or

prot

otyp

e

Page 4: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Fas

t rea

ctor

s to

dat

e

A

num

ber

of fa

st r

eact

ors

have

bee

n de

sign

ed/o

pera

ted

over

the

last

50

year

s–

Mos

t hav

e be

en r

esea

rch

or p

roto

type

rea

ctor

s–

Yet

to b

e su

cces

sful

ly c

omm

erci

aliz

ed

M

ajor

bot

tlene

cks

–C

apita

l cos

t–

Dem

onst

ratio

n of

saf

ety

LW

R p

erfo

rman

ce h

as b

enef

ited

trem

endo

usly

from

de

cade

s of

ope

ratio

nal e

xper

ienc

e

W

ant t

o us

e si

mul

atio

n to

gre

atly

acc

eler

ate

for

LMF

BR

s

Page 5: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P5

Det

ails

on

core

geo

met

ry

1/6

AB

TR

cor

e•

7k v

olum

es (c

ore,

ctr

l, re

flect

, shi

eld)

•43

k-5m

hex

ele

men

ts•~

6 G

B to

gen

erat

e us

ing

CU

BIT

217-

pin

fuel

ass

'y•

Con

form

al h

ex m

esh

•15

20 v

ols

•M

ultip

le h

omog

eniz

atio

n op

tions

, e.g

. pin

s re

solv

ed

Page 6: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wire

-Wra

pped

Fue

l Pin

Ass

embl

y(N

ear-

) E

xact

Geo

met

ry

•N

on-c

onfo

rmal

hex

mes

h•

Use

s “c

ompo

site

sur

face

s” fo

r si

des

of e

ach

unit

cell

•S

pace

-fill

ing

geom

etry

Page 7: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Clo

se-in

of w

ire-w

rapp

ed fu

el a

ssem

bly

-W

ire w

rap

used

to s

pace

pin

s-

Has

sig

nific

ant i

mpa

ct o

n pr

essu

re d

rop,

m

ixin

g, c

ross

flow

H

Fuel Pin

and Wire

Corner

Subchannel

Edge

Subchannel

Interior

Subchannel

Duct

Wall Fuel

Pin

D

P

Wire

Wrap

Page 8: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Cur

rent

sta

te o

f LM

FB

R m

odel

ing

T

wo

broa

d cl

asse

s of

pro

blem

s --

safe

ty a

nd d

esig

n

H

uge

rang

e of

pro

blem

s to

be

addr

esse

d w

ithin

the

se–

Mix

ing,

shi

eldi

ng, p

ower

gen

erat

ion,

str

uctu

ral f

eedb

ack,

fuel

dep

letio

n,

clad

ding

failu

re, t

rans

ient

ove

rpow

er, t

rans

ient

und

erco

olin

g, fi

ssio

n pr

oduc

t rel

ease

, sod

ium

boi

ling,

etc

etc

A

ll in

volv

e on

e or

sev

eral

of a

han

dful

of p

heno

men

a–

Com

plex

geo

met

ries

–N

eutr

on tr

ansp

ort

–C

onju

gate

hea

t tra

nsfe

r (lo

w P

r fo

r LM

FB

R, m

ostly

sin

gle

phas

e)–

Str

uctu

ral d

efor

mat

ion

–F

uel p

rope

rtie

s/be

havi

or (U

nal t

alk)

–Lo

ts o

f dat

a --

cros

s se

ctio

ns, d

iffus

iviti

es, e

tc.

>

100

0 pe

rson

-yea

rs o

f cod

es d

evel

oped

and

dep

loye

d in

70s

-80s

to

desi

gn e

arly

LM

FB

Rs

–M

any

code

s/m

odel

s ex

ist s

ince

mos

tly o

ne c

ode/

mod

el p

er p

heno

men

on

Page 9: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Rea

lly b

oilin

g it

dow

n

M

uch

of th

ese

phen

omen

a ad

dres

s tw

o ov

erar

chin

g pr

oble

ms

–D

emon

stra

te in

crea

se o

f lin

ear

pow

er to

mel

ting

–D

emon

stra

te u

npro

tect

ed

(pas

sive

) sa

fety

fea

ture

s

T

wo

appr

oach

es–

Adv

ance

d si

mul

atio

n le

ads

to

low

er r

ule-

of-t

hum

b de

sign

m

argi

ns fo

r ex

istin

g de

sign

s

–A

dvan

ced

sim

ulat

ion

lead

s to

de

sign

inno

vatio

ns w

ith m

uch

bette

r ec

onom

ics/

safe

ty

Impr

oved

Sim

ulat

ion

Val

idat

ion

and

Ope

ratin

g E

xper

ienc

e

Impr

oved

Des

ign

and

Sim

ulat

ion

Exp

erim

enta

l Unc

erta

inty

Ope

ratio

nal M

argi

n

Pre

dict

ion

Unc

erta

inty

Tem

pera

ture

Li

mit

Nom

inal

Pea

k Te

mpe

ratu

re

Ave

rage

Tem

pera

ture

Ope

ratin

g lim

it

Page 10: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

SH

AR

P -

-S

imul

atio

n-ba

sed

Hig

h-ef

ficie

ncy

Adv

ance

d R

eact

or P

roto

typi

ng

Exi

stin

g m

odel

s/fr

amew

ork

Page 11: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

SH

AR

P o

vera

ll f

ram

ewor

k

In

fast

rea

ctor

s, s

afet

y de

pend

s on

SM

-neu

tron

ics

feed

back

In

ther

mal

rea

ctor

s, T

H-n

eutr

onic

s fe

edba

ck s

igni

fican

t

Wan

t to

take

adv

anta

ge o

f too

ls d

evel

oped

els

ewhe

re–

Min

imiz

e re

quire

men

ts fo

r be

ing

used

in fr

amew

ork

& c

alcu

latio

ns•

Min

imal

cha

nges

to g

uts

of p

hysi

cs c

ode

–lib

rary

/driv

er•

Eac

h ph

ysic

s ca

n ch

oose

its

own

mes

h–

Cou

plin

g re

quire

s kn

owle

dge

of b

oth

mes

hes

& fi

elds

on

them

neu

tron

tra

nsp

ort

fuel

the

rmo

hydr

aul

ics

Str

uctu

ral

me

cha

nics

bala

nce

of

pla

nt

Cou

plin

g

Visu

aliz

atio

n

Mes

h ge

nera

tion

Hig

h-pe

rfor

man

ce i/

o

Ult

ra-s

cala

ble

solv

ers

•MC

•MO

L•D

ire

ct

Unc

erta

inty

Geo

met

ry

Ena

blin

g te

chno

logi

es

Page 12: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Nek

5000

& In

itial

The

rmal

Hyd

raul

ics

Sim

ulat

ion

Eff

ort

A

NL

code

for

fluid

s / h

eat t

rans

fer

(Fis

cher

, Lot

tes,

Tho

mas

)–

DN

S a

nd L

ES

–H

igh-

orde

r spe

ctra

l ele

men

t bas

ed c

ode

–S

cale

s to

P >

10,

000

proc

esso

rs–

Sta

te o

f the

art

mul

tigrid

sol

vers

–2

deca

des

of d

evel

opm

ent /

ver

ifica

tion

/ val

idat

ion

–S

uppo

rts

conj

ugat

e he

at tr

ansf

er, v

aria

ble

prop

ertie

s, M

HD

, ALE

, UR

AN

S

E

xten

sive

rea

ctor

TH

exp

erie

nce:

(Fan

ning

, Poi

nter

, Yan

g)–

RA

NS

mod

elin

g –

Sta

r C

D–

Sub

chan

nel c

odes

(S

AS

)

Page 13: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

UN

IC n

eutr

onic

s co

de

P

N2N

D

–S

cale

d to

64K

pro

cs o

n B

G/P

(m

ore

deta

il la

ter)

–E

ven-

parit

y se

cond

-ord

er f

orm

ulat

ion

–U

se s

pher

ical

har

mon

ics

to r

epre

sent

ang

ular

dis

trib

utio

n

–U

se fi

nite

ele

men

ts fo

r sp

atia

l app

roxi

mat

ion

–S

uper

ior

solu

tion

of h

omog

eneo

us p

robl

ems

S

N2N

D

–S

cale

d to

64K

prc

s on

BG

/P (

mor

e de

tail

late

r)

–E

ven-

parit

y se

cond

-ord

er f

orm

ulat

ion

–U

se d

iscr

ete

ordi

nate

s cu

batu

re t

o re

pres

ent

the

angu

lar

dist

ribut

ion

–U

se fi

nite

ele

men

ts fo

r sp

atia

l app

roxi

mat

ion

–P

rovi

des

chea

p m

emor

y m

atrix

met

hod

M

OC

FE

–Li

mite

d sc

alab

ility

in 3

d (1

00s

of p

rocs

)

–F

irst o

rder

inte

gral

tra

nspo

rt f

orm

ulat

ion

–U

se d

iscr

ete

ordi

nate

s cu

batu

re t

o re

pres

ent

the

angu

lar

dist

ribut

ion

–U

se fi

nite

ele

men

ts fo

r sp

atia

l app

roxi

mat

ion

–C

an h

andl

e th

ousa

nds

of g

roup

s du

e to

mat

rix fr

ee fo

rmul

atio

n

–S

houl

d be

sca

labl

e to

thou

sand

s of

pro

cess

ors

Page 14: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

The

rmo

mec

hani

cs m

odel

ing

Ju

st b

egin

ning

sim

ple

calc

ulat

ions

with

LLN

L co

de D

iabl

o

Li

ttle

fund

ing

so fa

r fo

r th

is c

ompo

nent

but

will

bec

ome

criti

cal i

n ne

ar

futu

re.

Page 15: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Add

ition

al to

ols/

tech

nolo

gies

use

d so

far

in S

HA

RP

M

eshi

ng -

-C

ubit

V

isua

lizat

ion

--V

isit

S

olve

rs -

-P

etsc

Cou

plin

g m

esh

repr

esen

tatio

n --

MO

AB

La

ngua

ge(s

): C

/FO

RT

RA

N m

ixed

with

MP

I

Page 16: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Pro

ject

goa

ls

W

hat w

e ar

e ju

dged

on

–C

arry

ing

out s

imul

atio

ns th

at p

redi

ct g

ener

al tr

ends

, elu

cida

te

fund

amen

tal p

heno

men

a, o

r m

ore

accu

rate

ly c

alcu

late

key

phy

sica

l qu

antit

ies

for

mor

e op

timiz

ed d

esig

n an

d lic

ensi

ng o

f SF

Rs.

V

ery

little

rew

ard

for

the

tool

itse

lf so

far

S

ome

rem

aini

ng s

kept

icis

m in

com

mun

ity (t

houg

h w

anin

g ra

pidl

y) th

at

adva

nced

sim

ulat

ion

is c

orre

ct a

ppro

ach

–Li

ttle

time

to r

espo

nsib

ly la

y gr

ound

wor

k fo

r a

long

er-t

erm

effo

rt if

not

un

iform

bel

ief i

n its

effe

ctiv

enes

s

B

ette

r ba

lanc

e m

ust b

e st

ruck

--

not a

ll of

f-th

e-sh

elf t

echn

olog

y ne

arly

go

od e

noug

h. M

ust p

ush

forw

ard

mat

h an

d cs

res

earc

h

Page 17: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Gen

eral

tool

s/te

chno

logi

es th

at w

e ar

e no

t fun

ded

to

purs

ue b

ut w

ould

hav

e bi

g im

pact

on

proj

ect

La

ngua

ges/

com

pile

rs w

ith m

ore

tran

spar

ency

in u

se o

f mem

ory

hier

arch

y

Q

uick

er to

ols

for

algo

rithm

ic p

roto

typi

ng/e

xplo

ratio

n be

yond

sin

gle

proc

M

orph

ing

of M

atla

b/V

isit

type

cap

abili

ties

for

anal

ysis

Q

uant

ifyin

g un

cert

aint

y fo

r m

ultip

hysi

cs c

oupl

ed s

imul

atio

ns

R

educ

tion

of c

ompl

exity

of c

reat

ing

deta

iled

mes

hes,

incl

udin

g cu

t-ce

ll te

chni

ques

, be

tter

mes

hing

tool

s/al

gorit

hms

A

goo

d op

en s

ourc

e pa

ralle

l cou

pler

that

doe

s w

hat

I nee

d it

to

M

ore

adva

nced

par

alle

l deb

uggi

ng to

ols

with

adv

ance

d m

emor

y sn

oopi

ng, e

tc.

F

aste

r co

mpu

ters

Page 18: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

App

licat

ion-

spec

ific

prob

lem

s w

here

gre

at a

pplie

d m

athe

mat

icia

ns a

re n

eede

d fo

r br

eakt

hrou

ghs

H

ighl

y sc

alab

le t

rans

port

met

hods

--

impr

oved

pre

cond

ition

ers

for

PN

, sca

laba

le r

ay tr

acin

g al

gorit

hms

for

deco

mpo

sed

geom

etrie

s, h

ybrid

met

hods

, sc

alab

le M

C e

tc. t

owar

ds a

sin

gle

reac

tor

anal

ysis

tool

for

VH

TR

, SF

R, L

WR

, etc

.

M

ulti-

scal

e ap

proa

ch f

or h

eat

tran

sfer

, tr

ansp

ort,

brid

ging

ab

initi

o to

eng

inee

ring

scal

e m

odel

ing

for

fuel

s, li

nkin

g D

NS

, RA

NS

, LE

S, a

nd s

ubch

anne

l, et

c.

A

dapt

ive

tran

spor

t m

etho

ds (

in e

nerg

y, a

ngle

, spa

ce,

and

poly

nom

ial o

rder

)

N

ew id

eas

beyo

nd m

ultig

roup

for

hand

ling

of e

nerg

y va

riabl

e

A

ccur

ate

coup

ling

tech

niqu

es f

or fa

st tr

ansi

ents

in r

eact

or a

ccid

ent

scen

ario

s

S

truc

ture

d C

FD

on

com

plex

geo

met

ries

C

ompo

nent

arc

hite

ctur

es f

or ti

ght/l

oose

cou

plin

g

D

eriv

ing

subg

rid fl

uid

mod

els

for

low

-PR

flo

ws,

sodi

um b

oilin

g fr

om D

NS

S

truc

tura

l mod

elin

g fo

r ro

d bo

win

g, v

esse

l exp

ansi

on,

etc.

Page 19: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wor

k co

nduc

ted

byA

NL

for t

he G

NE

P

Neu

tron

tran

spor

t alg

orith

ms

in d

epth

Page 20: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Hom

ogen

izat

ion

at v

ario

us le

vels

Hom

ogen

ized

as

sem

bly

Hom

ogen

ized

as

sem

bly

inte

rnal

s

Hom

ogen

ized

pi

n ce

llsF

ully

exp

licit

asse

mbl

y

Page 21: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Neu

tron

Tra

nspo

rt: T

wo

Bro

ad C

ateg

orie

s

S

toch

astic

(Mon

te C

arlo

)

Det

erm

inis

tic–

Eve

n P

arity

For

mul

atio

n (P

n-F

E)

–D

iscr

ete

Ord

inat

es (

Sn)

•S

atis

fy th

e tr

ansp

ort e

quat

ion

only

alo

ng s

ome

pred

eter

min

ed a

ngul

ar d

irect

ions

–In

tegr

al F

orm

(M

etho

d of

Cha

ract

eris

tics)

•R

ay tr

acin

g

•W

orks

wel

l in

low

den

sity

reg

ions

Page 22: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Mon

te C

arlo

Met

hods

F

ollo

w in

divi

dual

par

ticle

his

torie

s fr

om b

irth

(som

e so

urce

) to

dea

th

(abs

orpt

ion

and

leak

age)

N

ucle

ar d

ata

is e

xpre

ssed

in c

ontin

uum

of e

nerg

y

Abi

lity

to h

andl

e co

mpl

ex g

eom

etrie

s

Cal

cula

te in

tegr

al q

uant

ities

ove

r th

e w

hole

dom

ain

C

ons

–V

ery

time

cons

umin

g fo

r sc

atte

ring

dom

inan

t tra

nspo

rt (

e.g.

opt

ical

ly

thic

k m

ediu

m)

–N

ot a

ppro

pria

te w

hen

a de

taile

d so

lutio

n of

neu

tron

den

sity

th

roug

hout

the

geom

etry

is n

eede

d

Page 23: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Det

erm

inis

tic M

etho

ds

E

ffici

ent i

n sc

atte

ring

dom

inan

t situ

atio

ns

Now

can

han

dle

com

plex

geo

met

ries

(FE

M)

and

hete

roge

neou

s m

ater

ials

G

ive

deta

iled

solu

tions

thro

ugho

ut th

e do

mai

n

Con

s–

Mem

ory

inte

nsiv

e (s

even

dim

ensi

onal

pha

se s

pace

)–

Ene

rgy

varia

ble

hand

led

less

acc

urat

ely

(tha

n M

onte

Car

lo m

etho

ds)

–Lo

w d

ensi

ty r

egio

ns a

re p

robl

emat

ic fo

r se

cond

ord

er m

etho

ds

Page 24: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Som

e N

otes

on

Cro

ss S

ectio

ns

V

ital s

ourc

e of

inac

cura

cy in

det

erm

inis

tic c

odes

V

ery

invo

lved

pro

cess

to g

et c

ross

sec

tions

hom

ogen

ized

ove

r an

ene

rgy

grou

p–

All

the

phys

ics

know

ledg

e go

es h

ere

La

rge

num

ber

of e

nerg

y gr

oups

(~

10,0

00)

need

ed fo

r fa

st r

eact

ors

to

impr

ove

accu

racy

and

red

uce

unce

rtai

ntie

s

Nee

d to

rep

eat t

he c

ross

sec

tion

gene

ratio

n w

ith th

erm

al h

ydra

ulic

s fe

edba

ck (t

empe

ratu

re a

nd d

ensi

ty c

hang

es)

Page 25: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

The

Ste

ady

Sta

te T

rans

port

Equ

atio

n (p

46 in

Lew

is)

(,

)(

,)

(,

)f

rE

rE

rE

χν

Σr

rr

ˆˆ

ˆˆ

ˆˆ

(,

,)

(,

)(

,,

)(

,'

,'

)(

,',

')'

'

(,

)(

,')

(,

')(

,',

')'

'

ˆ(

,,

)

ts

f

rE

rE

rE

rE

Er

Ed

dE

rE

rE

rE

rE

ddE

k Sr

E

ψψ

ψ

χν

ψ

Ω⋅∇

Ω+

ΣΩ

Ω→

Ω→

ΩΩ

ΩΩ

∫∫

∫∫

rr

rr

rr

rr

rr

r

ˆ(

,,

)r

Ωr (

,)

tr

r ˆˆ

(,

',

')

sr

EE

ddE

ΣΩ

→Ω

→Ω

r

ˆ(

,,

)S

rE

Ω

The

neu

tron

flux

(ne

utro

n de

nsity

mul

tiplie

d by

spe

ed)

The

tota

l pro

babi

lity

of in

tera

ctio

n in

the

dom

ain

The

sca

tterin

g tr

ansf

er k

erne

l

The

ste

ady

stat

e m

ultip

licat

ive

fissi

on s

ourc

e

If a

fixed

sou

rce

is p

rese

nt th

en k

= 1

kT

he m

ultip

licat

ion

eige

nval

ue

Page 26: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Mul

tigro

up F

orm

alis

m

T

o da

te th

e fo

llow

ing

has

been

inef

fect

ive

–P

olyn

omia

l exp

ansi

ons

of th

e ne

utro

n flu

x de

pend

ence

–F

inite

ele

men

t exp

ansi

ons

of th

e ne

utro

n flu

x de

pend

ence

In

gen

eral

this

is m

easu

red

by th

e ga

in in

acc

urac

y re

lativ

e to

the

cost

as

soci

ated

with

the

solu

tion

algo

rithm

T

here

fore

, we

chos

e to

con

tinue

usi

ng th

e m

ultig

roup

form

alis

m

,,

''

'1

',

''

'1

ˆˆ

ˆˆ

ˆˆ

(,

)(

)(

,)

(,

')

(,

')'

()

()

()

(,

')'

ˆ(

,)

G

gt

gg

sg

gg

g

G

gg

fg

gg

g

rr

rr

rd

rr

rr

dk S

r

ψψ

ψ

χν

ψ

→=

=

Ω⋅∇

Ω+

ΣΩ

Ω→

ΩΩ

Ω

ΩΩ

∑∫

∑∫

rr

rr

rr

rr

rr

r

Page 27: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Sol

ving

the

Eig

enva

lue

Pro

blem

1A

TF

x

kψλ

−= = =

12

ˆˆ

ˆ(

,)

(,

)(

,)

T

Gr

rr

ψψ

ψψ

ΩΩ

rr

rL

Ax

=

,,

''

'1

ˆˆ

ˆˆ

ˆˆ

(,

)(

)(

,)

(,

')

(,

')'

G

gt

gg

sg

gg

g

Tr

rr

rr

ψψ

ψ→

=

⋅∇Ω

Ω−

ΣΩ

→Ω

ΩΩ

∑∫

rr

rr

rr

',

''

'1

ˆ(

)(

)(

)(

,')

'G

gg

fg

gg

Fr

rr

rd

ψχ

νψ

=

ΩΩ

∑∫

rr

rr

1T

Fk

ψψ

=

Ax

=

Sta

ndar

d ei

genv

alue

not

atio

n:

Cas

t the

tran

spor

t equ

atio

n as

a p

seud

o m

atrix

-vec

tor

oper

atio

n

T =

str

eam

ing/

colli

sion

/sca

tterin

g F

= fi

ssio

n

Page 28: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Eig

enva

lue

Sol

utio

n P

roce

ss (

Inve

rse

Pow

er M

etho

d)

1T

Fk F

ψψ

θψ

= =

()

1(

1)1

(1)

(1)

(1)

()

()

(1)

(1)

11

, ,

ii

ii

i

i

ii

i

FT

FT

kk

wk

kw

θθ

θ

θ θ−−

−−

−−

−−

==

=

Fis

sion

sou

rce

Last

equ

atio

n ha

s th

e ite

rativ

e so

lutio

n:

1

1 1

TF

k

Tk

kF

T

ψψ

ψθ

θθ

= = =

The

w is

an

arbi

trar

y ve

ctor

whi

ch w

e ch

oose

to b

e 1

such

that

we

get t

he to

tal f

issi

on s

ourc

e.

Page 29: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Neu

tron

ics

Cod

e S

olut

ion

Pro

cess

In

vers

ion

of T

is g

ener

ally

ver

y ex

pens

ive

due

to s

catte

ring

coup

ling.

R

ecas

t usi

ng th

e w

ithin

gro

up n

otat

ion

and

swee

p th

e gr

oups

–Lo

gica

l app

roac

h gi

ven

that

iter

atio

n on

fiss

ion

is a

lread

y ne

cess

ary

–“D

owns

catte

r” o

nly

regi

on h

as s

trai

ghtfo

rwar

d so

lutio

n (d

own

swee

p)–

“Ups

catte

r” re

gion

req

uire

s ad

ditio

nal i

tera

tion

(mor

e do

wn

swee

ps)

()

()

()

()

,,

ˆˆ

ˆˆ

ˆˆ

ˆ(

,)

()

(,

)(

,'

)(

,')

'(

,)

ii

ii

gt

gg

sg

gg

gr

rr

rr

dQ

ψψ

→Ω

⋅∇Ω

Ω=

ΣΩ

→Ω

ΩΩ

∫r

rr

rr

rr

()

()

,'

''

1,'

(1)

',

''

(1)

'1

ˆˆ

ˆˆ

(,

)(

,'

)(

,')

'

()

()

()

(,

')'

ˆ(

,)

ii

gs

gg

gg

Gg

g

Gi

gg

fg

gi

g

g

Qr

rr

d

rr

rr

dk S

r

ψ

χν

ψ

→∈ ≠

−−

=

Ω=

ΣΩ

→Ω

ΩΩ

ΩΩ

∑∫

∑∫

rr

r

rr

rr

r

Page 30: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Pic

king

a M

etho

d

Mon

te C

arlo

–U

ses

part

icle

“wal

king

” w

ith r

ando

m n

umbe

r de

cisi

ons

to d

ecid

e pa

th–

Has

bee

n im

plem

ente

d in

mul

ti-gr

oup

and

cont

inuo

us e

nerg

y

Firs

t ord

er d

iscr

ete

ordi

nate

s (m

atrix

free

)–

Dom

ain

is s

wep

t in

spec

ific

dire

ctio

ns, e

lem

ent b

y el

emen

t–

Ele

men

t siz

ed A

mat

rix is

form

ed a

nd in

vert

ed d

urin

g sw

eep

F

irst o

rder

met

hod

of c

hara

cter

istic

s (m

atrix

free

cp)

–S

erie

s of

par

alle

l tra

ject

orie

s ar

e us

ed to

pie

rce

the

dom

ain

–S

olut

ion

alon

g th

e ra

y is

che

ap a

nd s

ourc

e by

ele

men

t is

sim

ple

sum

S

econ

d or

der

disc

rete

ord

inat

es (g

ener

ally

a m

atrix

met

hod)

–B

lock

dia

gona

l mat

rix m

akes

met

hod

reas

onab

le to

sto

re

Sec

ond

orde

r sp

heric

al h

arm

onic

s (g

ener

ally

a m

atrix

met

hod)

–In

clud

es a

ll di

ffusi

on th

eory

met

hods

–S

tora

ge o

f mat

rices

is q

uite

exp

ensi

ve

Sec

ond

orde

r an

gula

r fin

ite e

lem

ents

–R

are

usag

e du

e to

com

plic

atio

n of

ani

sotr

opic

sca

tterin

g

Page 31: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Met

hods

Em

ploy

ed in

UN

IC

P

N2N

D–

Eve

n-pa

rity

seco

nd-o

rder

form

ulat

ion

–U

se s

pher

ical

har

mon

ics

to r

epre

sent

ang

ular

dis

trib

utio

n–

Use

fini

te e

lem

ents

for

spat

ial a

ppro

xim

atio

n–

Sup

erio

r sol

utio

n of

hom

ogen

eous

pro

blem

s

SN

2ND

–E

ven-

parit

y se

cond

-ord

er fo

rmul

atio

n–

Use

dis

cret

e or

dina

tes

cuba

ture

to r

epre

sent

the

angu

lar

dist

ribut

ion

–U

se fi

nite

ele

men

ts fo

r sp

atia

l app

roxi

mat

ion

–P

rovi

des

chea

p m

emor

y m

atrix

met

hod

M

OC

FE

–F

irst o

rder

inte

gral

tran

spor

t for

mul

atio

n–

Use

dis

cret

e or

dina

tes

cuba

ture

to r

epre

sent

the

angu

lar

dist

ribut

ion

–U

se fi

nite

ele

men

ts fo

r sp

atia

l app

roxi

mat

ion

–C

an h

andl

e th

ousa

nds

of g

roup

s du

e to

mat

rix fr

ee fo

rmul

atio

n–

Sho

uld

be s

cala

ble

to th

ousa

nds

of p

roce

ssor

s

Page 32: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Sec

ond

Ord

er M

etho

ds; W

ithin

Gro

up F

orm

ulat

ion

Ang

ular

flux

is w

ritte

n in

term

s of

eve

n-an

d od

d-pa

rity

com

pone

nts

ˆˆ

ˆ(

,)

(,

)(

,)

gg

gr

rr

ψψ

ψ+

−Ω

rr

r

ˆˆ

ˆˆ

(,

)(

)(

,)

(,

)(

,)

gt

gg

gg

rr

rW

rQ

ψ−

++

⋅∇Ω

Ω=

Ω+

Ωr

rr

rr

r

ˆˆ

ˆˆ

(,

)(

)(

,)

(,

)(

,)

gt

gg

gg

rr

rW

rQ

ψ+

−−

−Ω

⋅∇Ω

Ω=

Ω+

Ωr

rr

rr

r

Eve

n-P

arity

Odd

-Par

ity

Eve

n-an

d od

d-pa

rity

form

s of

the

tran

spor

t equ

atio

n ar

e ob

tain

ed

11

22

ˆˆ

ˆ(

,)

(,

)(

,)

gg

gQ

rQ

rQ

Ω=

Ω±

−Ωr

rr

,

,,

ˆˆ

ˆˆ

ˆ(

,)

(,

')(

,')

'

ˆˆ

ˆˆ

()

(')

(,

')'

gs

gg

g

sg

gm

mg

m

Wr

rr

d

rP

rd

ψ

ψ

±±

±→ ±

±±

Ω=

ΣΩ

⋅ΩΩ

Ω

Ω⋅Ω

ΩΩ

∫ ∑ ∫

rr

r

rr

With

in g

roup

Sca

tterin

g

Ext

erna

l Sou

rce

Page 33: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

PN

2ND

,,

,0

,2

ˆˆ

(,

)(

)(

)(

)(

)L

lT

gl

mg

lm

gl

ml

rY

rr

ψψ

ψ+

++

+=

=−

Ω=

Ω=

Ω∑∑

rr

rY

,,

,1,

3

ˆˆ

(,

)(

)(

)(

)(

)L

lT

gl

mg

lm

gl

ml

rY

rr

ψψ

ψ−

−−

−=

=−

Ω=

Ω=

Ω∑∑

rr

rY

Sph

eric

al h

arm

onic

s ap

prox

imat

ion

Fin

ite e

lem

ent a

ppro

xim

atio

n ˆ(

,)

()

()

TT

gg

rL

ψ±

±±

Ω=

Ω⊗

rr

Y

Page 34: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

SN

2ND

,,0

,0ˆ (

)l

mn

nl

mn

Yw

δδ

Ω=

,

,,

ˆˆ

(,

)(

)(

)

ˆ(

)

ˆ(

)

TT

gg

Tg

ng

nn

gn

SNP

NP

N

nn

nrL

r

wM N

ψψ

ψϕ

ϕ

++

+

++

++

+

++

++

+

Ω=

Ω⊗

=

=

rr

Y

Y Y

,(

,)

(,

)(

)T

gg

ng

nr

rL

ϕϕ

++

⇒Ω

=r

rr

Dis

cret

e or

dina

tes

appr

oxim

atio

n

ˆ(

,)

()

()

TT

gg

rL

ψ−

−−

Ω=

Ω⊗

rr

Y

Page 35: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

PN

2ND

& S

N2N

D G

over

ning

Equ

atio

ns ()1

,,

,g

mt

sg

gm

−−

→Ξ

−Σ

'1,

:'

gG

RU

LE

gg

∈ ≠P

Ng

gg

gA

QQ

ψ+

+−

=+

()

()

()

()

()

()

(1)

,,

'',

,,

',',

,(

1)'

1

()

()

()

,,

,,

,,

,,

,,

()

()

,,

,'

,',

,,

,,

1G

ii

ig

es

gg

eg

eg

ef

ge

eg

ee

ge

iR

UL

Eg

iT

Ti

ig

em

gm

KL

eK

Lg

eg

mg

em

mK

L

ii

Tg

eg

ms

gg

mg

em

gm

Ke

KL

gm

RU

LE

QF

JF

IF

Sk

VV

PQ

QV

US

ψχ

νψ

ξψ

ξ

++

++

+−

++

→−

=

−+

−−

−→

⊗⊗

+

Σ+

Ξ

∑∑

∑ ∑(

),

ie

PN

2ND

SN

2ND

()1

,g

mt

−Ξ

:'

1,R

UL

Eg

G∈

Gro

up s

ourc

e eq

uatio

ns

()

SN

gg

gg

gg

AN

QQ

M

ϕ

ψϕ

++

−+

++

+=+

=

Page 36: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Gro

up S

wee

ping

Alg

orith

m

()

1

''

&'

1,

gg

gg

gg

Solv

eA

QQ

Upd

ate

QQ

gG

ψ+

−+

+−

=+

()

()

12

11

22

()

1

()

()

()

1(

1)

''

&'

1,

ig

gg

gg

ii

ii

gg

gS

gg

gg

Solv

eM

MA

QQ

Solv

eF

Upd

ate

QQ

gG

ψϕ

ψψ

αψ

ψ

−+

+−

+−

++

−−

++

−+

+−

+−

==

+

=+

()

1

''

&'

1,

gg

gg

gg

Solv

eA

QQ

Upd

ate

QQ

gG

ψ+

−+

+−

=+

()

()

1 2

11

22

()

1

()

()

()

1(

1)

''

&'

1,

ig

gg

gg

ii

ii

gg

gS

gg

gg

Solv

eM

MA

QQ

Solv

eF

Upd

ate

QQ

gG

ψϕ

ψψ

αψ

ψ

−+

+−

+−

++

−−

++

−+

+−

+−

==

+

=+

Dow

nsca

tter

only

reg

ime

Ups

catte

r reg

ime

Cnv

g or

Max

Iter

No

Yes

Sta

rt

End

PN

2ND

Ups

catte

r reg

ime

Cnv

g or

Max

Iter

No

Yes

End

Dow

nsca

tter

only

reg

ime

Sta

rtS

N2N

D

Page 37: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Fea

ture

s of

Sec

ond

Ord

er F

orm

Sol

utio

ns in

UN

IC

P

N2N

D a

nd S

N2N

D s

olve

rs h

ave

been

dev

elop

ed to

sol

ve th

e st

eady

-sta

te, s

econ

d-or

der,

eve

n-pa

rity

neut

ron

tran

spor

t equ

atio

n–

PN

2ND

: Sph

eric

al h

arm

onic

met

hod

in 1

D, 2

D a

nd 3

D g

eom

etrie

s w

ith F

E m

ixed

m

esh

capa

bilit

ies

–S

N2N

D: D

iscr

ete

ordi

nate

s in

2D

and

3D

geo

met

ries

with

FE

mix

ed m

esh

capa

bilit

ies

T

hese

sec

ond

orde

r m

etho

ds h

ave

been

impl

emen

ted

on la

rge

scal

e pa

ralle

l mac

hine

s–

Line

ar te

trah

edra

l and

qua

drat

ic h

exah

edra

l ele

men

ts–

Fix

ed s

ourc

e an

d ei

genv

alue

pro

blem

s–

Arb

itrar

ily o

rient

ed r

efle

ctiv

e an

d va

cuum

bou

ndar

y co

nditi

ons

–P

ET

Sc

solv

ers

are

utili

zed

to s

olve

with

in-g

roup

equ

atio

ns•

Con

juga

te g

radi

ent m

etho

d w

ith S

SO

R a

nd IC

C p

reco

nditi

oner

s•

Oth

er s

olut

ion

met

hods

and

pre

cond

ition

ers

will

be

inve

stig

ated

–S

ynth

etic

diff

usio

n ac

cele

ratio

n fo

r w

ithin

-gro

up s

catte

ring

itera

tion

–P

ower

iter

atio

n m

etho

d fo

r ei

genv

alue

pro

blem

•V

ario

us a

ccel

erat

ion

sche

mes

are

bei

ng in

vest

igat

ed–

MeT

iS is

em

ploy

ed fo

r m

esh

part

ition

ing

Page 38: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

U

nstr

uctu

red

finite

ele

men

t mes

hes

are

empl

oyed

–C

UB

IT p

acka

ge is

the

prim

ary

mes

h ge

nera

tion

tool

–he

xahe

dral

and

tetr

ahed

ral e

lem

ents

(lin

ear

and

quad

ratic

)–

Fur

ther

res

earc

h is

req

uire

d fo

r re

duci

ng m

esh

gene

ratio

n ef

fort

s an

d ro

bust

mer

ging

of t

he m

eshe

s of

indi

vidu

al g

eom

etric

al c

ompo

nent

s

Gen

eral

Geo

met

ry C

apab

ility

in U

NIC

–A

BT

R A

ssem

bly

Page 39: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Key

Fea

ture

s of

the

Impl

emen

tatio

n S

trat

egy

F

ollo

w th

e “o

wne

r co

mpu

tes”

rule

und

er th

e du

al c

onst

rain

ts o

f min

imiz

ing

the

num

ber

of

mes

sage

s a

nd o

verla

ppin

g co

mm

unic

atio

n w

ith c

ompu

tatio

n

Eac

h pr

oces

sor “

ghos

ts” i

ts s

tenc

il de

pend

ence

s in

its

neig

hbor

s

Gho

st n

odes

ord

ered

afte

r con

tiguo

us o

wne

d no

des

D

omai

n m

appe

d fr

om (u

ser)

glo

bal o

rder

ing

into

loca

l ord

erin

gs

Sca

tter/

gath

er o

pera

tions

cre

ated

bet

wee

n lo

cal s

eque

ntia

lve

ctor

s an

d gl

obal

di

strib

uted

vect

ors,

bas

ed o

n ru

ntim

e co

nnec

tivity

pat

tern

s

Kry

lov-

Sch

war

z op

erat

ions

tran

slat

ed in

to lo

cal t

asks

and

com

mun

icat

ion

task

s

Pro

filin

g us

ed to

hel

p el

imin

ate

perf

orm

ance

bot

tlene

cks

in c

omm

unic

atio

n an

d m

emor

y hi

erar

chy

Page 40: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Impr

oved

Par

alle

lism

and

Acc

eler

atio

n

R

ecen

tly a

dded

cap

abili

ty to

par

alle

lize

by s

pace

, ang

le, a

nd e

nerg

y in

UN

IC–

Pre

viou

s im

plem

enta

tion

only

con

side

red

spat

ial p

aral

leliz

atio

n–

Mem

ory

limita

tions

pre

vent

ed la

rge

prob

lem

s fr

om b

eing

exe

cute

d

Im

plem

ente

d m

atrix

-fre

e C

G s

olve

rs fo

r P

N2N

D a

nd S

N2N

D–

New

ver

sion

use

s si

ngle

ste

ncile

d pr

econ

ditio

ner

mat

rix fo

r ea

ch a

ngle

-gr

oup

part

ition

(fa

r le

ss m

emor

y)–

Par

titio

ns c

an b

e so

lved

sim

ulta

neou

sly

–C

urre

nt fi

ssio

n so

urce

iter

atio

n sc

hem

e st

ill u

ses

Gau

ss S

eide

l in

ener

gy

Add

ed fi

ssio

n so

urce

acc

eler

atio

n–

Tche

bych

ev–

Sel

f-ad

just

ing

with

in-g

roup

flux

err

or

tole

ranc

e to

min

imiz

e pr

econ

ditio

ner

effo

rt–

Tim

e to

sol

utio

n re

duce

d by

10+

fact

or

Page 41: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Sam

ple

Per

form

ance

of A

ccel

erat

ion

Sch

emes

-T

aked

a B

ench

mar

k 4

1.E

-08

1.E

-07

1.E

-06

1.E

-05

1.E

-04

1.E

-03

1.E

-02

1.E

-01

1.E

+00

02

46

810

1214

1618

2022

24O

uter

Iter

atio

n

Error

Eig

enva

lue

Fis

sion

Flu

xG

roup

1G

roup

2G

roup

3G

roup

4

1.E

-08

1.E

-07

1.E

-06

1.E

-05

1.E

-04

1.E

-03

1.E

-02

1.E

-01

1.E

+00

02

46

810

1214

1618

2022

24O

uter

Iter

atio

n

Error

Eig

enva

lue

Fis

sion

Flu

xG

roup

1G

roup

2G

roup

3G

roup

4

`

With

out T

cheb

yche

v ac

cele

ratio

n an

d a

fixed

tole

ranc

e of

with

in-g

roup

flu

x er

ror

With

Tch

ebyc

hev

acce

lera

tion

and

self-

adju

stin

g w

ithin

-gro

up f

lux

erro

r to

lera

nce

Page 42: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Ene

rgy

Gro

up P

aral

lelis

m Is

sues

Sod

ium

Fas

t Rea

ctor

Fue

l A

ssem

bly

(230

Gro

ups)

PW

R F

uel A

ssem

bly

(172

G

roup

s)

Sca

tterin

g C

ross

Sec

tion

Ste

ncili

ng

Page 43: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

k-E

igen

valu

e P

ower

Iter

atio

n

S

tead

yst

ate

mul

tigro

upei

genv

alue

and/

orfix

edso

urce

itera

tions

for

one,

two,

and

thre

edi

men

sion

alun

stru

ctur

edfin

iteel

emen

tm

esh

geom

etrie

s.

Mai

nlo

op(P

ower

itera

tion)

Beg

inO

uter

Itera

tion

Beg

inLo

opov

eren

ergy

grou

psO

btai

ngr

oup

scat

terin

g+fis

sion

+fix

edso

urce

sS

olve

asy

mm

etric

posi

tive

defin

itelin

ear

syst

emfo

rflu

x(p

reco

nditi

oned

conj

ugat

egr

adie

nt)

End

Loop

over

ener

gygr

oups

Com

pute

tota

lfis

sion

sour

ceC

heck

for

conv

erge

nce

inei

genv

alue

,ang

ular

flux,

and

sour

ces

End

Out

erIte

ratio

n

Page 44: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Res

ourc

e R

equi

rem

ents

for

UN

ICS

tora

ge (

PN

2ND

Sol

ver)

M

assi

ve li

near

sys

tem

s

N e

nerg

y gr

oups

, m m

esh

poin

ts, q

ang

ular

term

s, a

nd p

non

zero

es p

er

row

, we

need

m∗q

∗p ∗8

∗1.

5 by

tes

are

requ

ired

to s

tore

the

mat

rix in

co

mpr

esse

d ro

w fo

rmat

.

Sin

ce th

is is

a s

ymm

etric

mat

rix, w

e ne

ed h

alf o

f thi

s.

As

an e

stim

ate,

for

4000

non

zero

es in

eac

h ro

w (

p) fo

r 10

8ro

ws

(m =

106

and

q =

100

):–

2.4

tera

byte

s (T

B)

of m

emor

y pe

r gr

oup

for

the

mat

rix a

lone

(80

0 M

B fo

r on

e ve

ctor

) an

d 24

pet

abyt

es (

PB

) fo

r 10

,000

gro

ups.

Page 45: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Res

ourc

e R

equi

rem

ents

for

UN

ICP

erfo

rman

ce –

A C

rude

Ana

lysi

s

T

he c

onju

gate

gra

dien

t (C

G)

met

hod

is O

[n ∗

i] w

here

n

= n

umbe

r of

non

zer

oes

in th

e m

atrix

(p ∗m

∗q)

. For

a w

ell c

ondi

tione

d sy

stem

, the

num

ber

of it

erat

ions

(i)

need

ed to

con

verg

e is

sm

all.

M

atrix

vec

tor

prod

uct d

omin

ates

the

exec

utio

n tim

e–

Tw

o m

atrix

-vec

tor

prod

ucts

per

CG

iter

atio

n–

2 ∗n

floa

ting

poin

t ope

ratio

ns (f

lops

) ne

eded

for

each

mat

rix v

ecto

r pr

oduc

t–

Neg

lect

the

vect

or o

pera

tions

(dot

pro

duct

s an

d sc

ale)

for

seria

l cas

e si

nce

(n >

> m∗q

)

Page 46: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Res

ourc

e R

equi

rem

ents

for

UN

ICP

erfo

rman

ce (c

ontd

.)

F

or i

itera

tions

of C

G, O

out

er it

erat

ions

, and

N g

roup

s (a

ssum

ing

the

sam

e nu

mbe

r of i

nner

iter

atio

ns fo

r al

l the

gro

ups)

, the

tota

l flo

ps a

re 4

∗n∗

i ∗N

∗O

.

CG

per

form

ance

is m

emor

y ba

ndw

idth

lim

ited

–10

-20

% o

f mac

hine

pea

k is

pra

ctic

al

For

i =

100

, O =

50,

N =

10,

000,

and

n =

4∗1

011, t

he to

tal w

ork

is 8

x1019

flops

(80,

000

peta

flops

)–

At 1

00 T

Flo

p/s,

111

1 hr

s–

At 1

PF

lops

/s, 1

11 h

rs

Page 47: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Ben

chm

ark

Pro

blem

Usi

ng U

NIC

PN

2ND

–Z

PP

R-1

5 C

ritic

al E

xper

imen

tM

esh

with

76,

000

vert

ices

, P3

scat

terin

g ke

rnel

and

230

ene

rgy

grou

ps

Com

puta

tiona

l Mes

h an

d E

xam

ple

Flu

x S

olut

ions

of Z

PP

R-1

5 C

ritic

al E

xper

imen

t

Flu

x ex

pans

ion

orde

rS

catte

ring

ord

erE

igen

valu

e

P1

P1

0.99

258

P3

P3

0.99

640

P5

P3

0.99

651

Mon

te C

arlo

(VIM

)0.

9964

7±0.

0001

0

Page 48: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Pow

er D

istr

ibut

ion

for

AB

TR

Ful

l Cor

e B

ench

mar

k

Sam

ple

UN

IC s

olut

ion

for A

BT

R.

(Lef

t) M

eTiS

dec

ompo

sitio

n fo

r 51

2 pr

oces

sors

(cen

ter)

hom

ogen

ized

fuel

reg

ion

s ar

e ex

trac

ted

and

disp

lay

the

pow

er d

istr

ibut

ion

whe

re

the

low

er

rem

nant

dis

play

s th

e M

eTiS

dec

ompo

sitio

n an

d (r

ight

) ve

rtic

al

slic

e th

roug

h th

e m

odel

sho

win

g th

e po

wer

dis

trib

utio

n.

Gro

up 1

Flu

x

Pow

er D

istr

ibut

ion

Page 49: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Per

form

ance

of U

NIC

(P

N2N

D)

on C

ray

XT

4

P

aral

lel p

erfo

rman

ce fr

om 5

12 to

409

6 C

ray

XT

4 pr

oces

sors

–12

0ºpe

riodi

c A

BT

R c

ore

with

hom

ogen

ized

ass

embl

ies

–33

gro

up P

5ca

lcul

atio

n–

Mes

h co

ntai

ns 5

87,4

58 q

uadr

atic

tetr

ahed

ral e

lem

ents

and

793

,668

ver

tices

•A

bout

12

mill

ion

spac

e-an

gle

degr

ees

of fr

eedo

m p

er e

nerg

y gr

oup

–A

bout

900

GF

lop/

s (~

4.2%

of m

achi

ne p

eak)

on

4,09

6 pr

oces

sors

Pro

cess

ors

AggregateGFlop/s

10

00

20

00

30

00

40

00

10

0

20

0

30

0

40

0

50

0

60

0

70

0

80

0

90

0

10

00

Page 50: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Per

form

ance

bot

tlene

cks

V

ecto

r dot

pro

duct

s–

14%

-29%

–Lo

ad im

bala

nce

T

otal

line

ar it

erat

ion

coun

t–

Incr

ease

s as

we

grow

the

num

ber

of p

roce

ssor

s

Pro

cess

ors

%ofTimeonVectorDotProducts

1000

2000

3000

4000

1012141618202224262830

Pro

cess

ors

TotalLinearIterations

1000

2000

3000

4000

5000

6000

0

6500

0

7000

0

7500

0

8000

0

Page 51: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Ang

ular

Con

verg

ence

of E

igen

valu

e of

AB

TR

Cor

e U

sin

g U

NIC

on

Blu

eGen

e/P

S

N2N

D S

olve

r

–9

ener

gy g

roup

s

–M

esh

(ass

embl

y ho

mog

eniz

ed)

•18

7,56

0 he

xahe

dral

qua

drat

ic e

lem

ents

and

785

,801

ver

tices

Spr

ead

over

512

pro

cess

or c

ores

Pro

cess

orC

ores

Ang

ula

rR

esol

utio

nA

ngle

sin

Spa

ce-A

ngle

DO

FE

igen

valu

e

2,04

81

43,

143,

204

1.00

633

4,60

82

97,

072,

209

1.00

823

8,19

23

1612

,572

,816

1.00

754

12,8

004

2519

,645

,025

1.00

776

18,4

325

3628

,288

,836

1.00

773

25,0

886

4938

,504

,249

1.00

781

32,7

687

6450

,291

,264

1.00

780

41,4

728

8163

,649

,881

1.00

782

51,2

009

100

78,5

80,1

001.

0078

1

61,9

5210

121

95,0

81,9

211.

0078

2

73,7

2811

144

113,

155,

344

1.00

782

Page 52: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wea

k S

calin

g of

UN

IC o

n B

lueG

ene/

P

S

N2N

D S

olve

r

2,04

8 to

73,

728

Cor

es (

Virt

ual N

ode

Mod

e)

Page 53: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wea

k S

calin

g of

UN

IC o

n B

lueG

ene/

P (

cont

d.)

Lo

ad im

bala

nce

in r

educ

e op

erat

ions

N

eed

to b

alan

ce b

ound

ary

vert

ices

Page 54: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Thr

ee F

unda

men

tal L

imiti

ng F

acto

rs to

Pea

k P

erfo

rma

nce

M

emor

y B

andw

idth

–P

roce

ssor

doe

s no

t get

dat

a at

the

rate

it r

equi

res

In

stru

ctio

n Is

sue

Rat

e–

If th

e lo

ops

are

load

/sto

re b

ound

, we

will

not

be

able

to d

o a

float

ing

poin

t ope

ratio

n in

eve

ry c

ycle

eve

n if

the

oper

ands

are

ava

ilabl

e in

pr

imar

y ca

che

–S

ever

al c

onst

rain

ts (l

ike

prim

ary

cach

e la

tenc

y, la

tenc

y of

floa

ting

poin

t uni

ts e

tc.)

are

to b

e ob

serv

ed w

hile

com

ing

up w

ith a

n op

timal

sc

hedu

le

Fra

ctio

n of

Flo

atin

g P

oint

Ope

ratio

ns–

Not

eve

ry in

stru

ctio

n is

a fl

oatin

g po

int i

nstr

uctio

n

Page 55: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Pat

h fo

rwar

d

Lo

ad b

alan

cing

to b

e ha

ndle

d th

roug

h be

tter

part

ition

ing

P

aral

leliz

e ac

ross

gro

ups

to in

crea

se th

e am

ount

of c

oncu

rren

cy

Exp

lore

the

hybr

id (

mix

ed M

PI/O

penM

P)

prog

ram

min

g m

odel

–B

ette

r al

gorit

hmic

con

verg

ence

rate

M

emor

y re

duci

ng a

lgor

ithm

s fo

r m

atrix

vec

tor

prod

ucts

–T

enso

r m

atrix

vec

tor

prod

uct i

mpl

emen

tatio

n

Mor

e ef

ficie

nt c

usto

m p

reco

nditi

oner

s th

at ta

ke a

dvan

tage

of t

he m

atrix

sp

arsi

ty p

atte

rn

Page 56: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Wire

-Wra

pped

Fue

l Pin

Ass

embl

yS

etup

Bot

tlene

cks

C

AD

-bas

ed g

eom

etry

def

initi

on s

urpr

isin

gly

diffi

cult

–“s

wee

p w

ith r

otat

ion”

not

sup

port

ed/r

obus

t

Var

ious

pie

ces

of th

e pr

oces

s br

oke,

forc

ing

mor

e de

com

posi

tion

–S

wep

t+ro

tate

d su

rfac

e, v

olum

e m

esh

N

o w

ay to

ana

lytic

ally

spe

cify

geo

met

ry o

r m

esh,

th

ough

bot

h co

ncep

tual

ly s

trai

ghtfo

rwar

d

MA

TLA

B-b

ased

sol

utio

n no

t sca

labl

e, p

orta

ble,

ex

tens

ible

–37

pin

, 217

pin

pro

blem

s ne

eded

too

R

eal g

eom

etry

wou

ld h

elp

with

vol

ume

frac

tion

calc

ulat

ion

for

wire

hom

ogen

izat

ion

Page 57: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

App

roac

hes

to T

H a

naly

sis

of s

ubas

sem

blie

s

D

NS

–di

rect

num

eric

al s

imul

atio

n of

all

scal

es

pa

ram

eter

-fre

e

LE

S –

larg

e ed

dy s

imul

atio

n +

dis

sipa

tion

pa

ram

eter

-fre

e

R

AN

S –

Rey

nold

s-av

erag

ed N

avie

r-S

toke

stu

ning

requ

ired

S

ubch

anne

l mod

elin

gem

piric

al in

put

40

0 x

200

subc

hann

els

in th

e co

re:

–S

ubch

anne

l ana

lysi

s w

ill c

ontin

ue to

be

used

for

reac

tor

desi

gn.

–R

AN

S w

ill in

form

des

ign

proc

ess.

–LE

S c

an h

elp

to v

alid

ate

/ inf

orm

RA

NS

and

sub

chan

nel a

naly

sis.

H

iera

rchi

cal a

ppro

ach

yiel

ds in

depe

nden

t/red

unda

nt re

fere

nce

calc

ulat

ionsim

prac

tical

107

p. p

er c

hann

el

105

p. p

er c

hann

el–

stea

dy s

tate

100

p. p

er c

hann

el–

stea

dy s

tate

Page 58: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

Oct

ober

4, 2

007

GN

EP

Ann

ual R

evie

w M

eetin

g

App

roac

hes

to T

H a

naly

sis

of s

ubas

sem

blie

s

D

NS

–di

rect

num

eric

al s

imul

atio

n of

all

scal

es

p

aram

eter

-fre

e

LE

S –

larg

e ed

dy s

imul

atio

n +

diss

ipat

ion

pa

ram

eter

-fre

e

R

AN

S –

Rey

nold

s-av

erag

ed N

avie

r-S

toke

stu

ning

req

uire

d

S

ubch

anne

l mod

elin

gem

piric

al in

put

40

0 x

200

subc

hann

els

in th

e co

re:

–S

ubch

anne

l ana

lysi

s w

ill c

ontin

ue t

o be

use

d fo

r re

acto

r de

sign

.

–R

AN

S w

ill in

form

des

ign

proc

ess.

–LE

S c

an h

elp

to v

alid

ate

/ inf

orm

RA

NS

and

sub

chan

nel a

naly

sis.

H

iera

rchi

cal a

ppro

ach

yiel

ds in

depe

nden

t/red

unda

nt

refe

renc

e ca

lcul

atio

ns

impr

actic

al

107

p. p

er c

hann

el

105

p. p

er c

hann

el–

stea

dy s

tate

100

p. p

er c

hann

el–

stea

dy s

tate

Page 59: h questions History, current state of the art, and open researc · 2008. 10. 8. · rs for PN, scalabale ray tracing algorithms for decomposed geometries, hybrid methods, scala ble

SH

AR

P fr

amew

ork

Set

up B

ottle

neck

s

In

tero

pera

bilit

y cr

ucia

l–

Inte

ract

ing

with

mul

tiple

mod

ules

–N

eed

varie

ty o

f too

ls to

ope

rate

on

mes

h &

fiel

d da

ta

Cou

plin

g re

quire

s m

eshe

s &

res

ults

in th

e sa

me

plac

e

Cen

tral

ized

par

alle

l mes

h in

fras

truc

ture

nee

ded,

to s

uppo

rt c

oupl

ing

whi

le

allo

win

g m

odul

es fr

eedo

m

Met

adat

a ne

eded

to c

oord

inat

e co

uplin

g (n

orm

aliz

atio

n/co

nser

vatio

n)