In el-oneAPI pa a Compu ación He e ogénea
In el-oneAPI o He e ogeneous Compu ing
Ge mán Cas año Roldán
T abajo de fin de g ado del G ado en Ingenie ía In o má ica, Facul ad de
In o má ica, Uni e sidad Complu ense de Mad id
Cu so 2020/2021
Di ec o :
Ca los Ga cía Sánchez
In el-oneAPI o He e ogeneous Compu ing
Índice
Acknowledgmen s 3
Resumen 4
Palab as Cla e 4
Abs ac 5
Key Wo ds 5
Chap e 1: In oduc ion 6
Wo k plan 7
Lea ning phase 7
Mig a ion phase 7
Benchma king phase 7
Chap e 2: Mo i a ion and Objec i es 8
Mo i a ion 8
Objec i es 10
Chap e 3: S a e o he A 10
CUDA 11
CUDA Al e na i es 12
High-Le el P og amming 12
OpenMP 12
OpenACC 12
C++ Lib a ies and Ex ensions 13
Py hon and Ja a 13
SYCL and oneAPI 13
FPGAs 15
Fu u e Accele a o s 15
Chap e 4: DPC++ 16
Asynch onous excep ions 16
De ice Selec o 17
Buffe s and Accesso s 18
Unified Sha ed Memo y 19
Queue and pa allel_ o 19
Chap e 5: DPCT & Rodinia 21
DPC++ Compa ibili y Tool 21
Rodinia Benchma ks 22
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In el-oneAPI o He e ogeneous Compu ing
Chap e 6: Me hodology 24
Mig a ion p ocess 24
Benchma king p ocess 29
Ins umen aliza ion 30
CUDA s oneAPI 30
P ofiling 31
O he a chi ec u es 32
Chap e 7: Mig a ion Resul s 33
Wa nings 33
Manual modifica ions 37
P oblems encoun e ed 39
Chap e 8: Pe o mance Resul s 41
Pe o mance o he memo y ope a ions 41
Pe o mance o he ke nel execu ion 42
O e all pe o mance 48
Chap e 9: Conclusions 49
Bibliog aphy 51
Glossa y 54
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In el-oneAPI o He e ogeneous Compu ing
Acknowledgmen s
Fo emos , I would like o hank my di ec o in his p ojec , Ca los Ga cía Sánchez, no only
o his suppo and guidance bu o a ousing my in e es in he e ogeneous compu ing
du ing he subjec "P og amación de GPUs y Acele ado es", wi hou which I wouldn' ha e
chosen a p ojec like his o my final deg ee p ojec .
I also would like o exp ess my g a i ude o Alina Shad ina om In el o he in e es and he
insigh p o ided when p oblems a ose du ing he mig a ion om CUDA o oneAPI.
3
In el-oneAPI o He e ogeneous Compu ing
Resumen
"oneAPI es un modelo de p og amación unificado, abie o y basado en es ánda es,
que o ece una expe iencia de desa ollado común en odas las a qui ec u as de
acele ado es, pa a un endimien o de aplicaciones más ápido, más p oduc i idad y una
mayo inno ación."
-www.oneapi.com
La he amien a de compa ibilidad DPC++ de In el es un componen e del oneAPI Base
Toolki . es a he amien a ans o ma au omá icamen e código CUDA en Da a Pa allel C++
(DPC++) ayudando en el p oceso de mig ación.
Es e p oyec o consis e en un análisis de la he amien a de compa ibilidad DPC++,
conside ando la in e ención manual eque ida y los p oblemas encon ados al mig a los
benchma ks de Rodinia. Y un es udio compa a i o del endimien o ob enido po el código
mig ado.
Palab as Cla e
In el oneAPI, SYCL, Da a Pa allel C++, He amien a de compa ibilidad Da a Pa allel, CUDA,
Compu ación he e ogénea, Rodinia Benchma k Sui e.
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In el-oneAPI o He e ogeneous Compu ing
Abs ac
"oneAPI is a c oss-indus y, open, s anda ds-based unified p og amming model ha
deli e s a common de elope expe ience ac oss accele a o a chi ec u es— o as e
applica ion pe o mance, mo e p oduc i i y, and g ea e inno a ion."
-www.oneapi.com
The In el DPC++ Compa ibili y Tool is a componen o he In el oneAPI base oolki . This
ool au oma ically ans o ms CUDA code in o Da a Pa allel C++ (DPC++) assis ing in he
mig a ion p ocess.
This p ojec consis s o an analysis o he DPC++ Compa ibili y Tool, conside ing he
manual in e en ion equi ed and he p oblems encoun e ed while mig a ing he Rodinia
benchma ks. And a compa a i e s udy o he pe o mance ob ained by he mig a ed code.
Key Wo ds
In el oneAPI, SYCL, Da a Pa allel C++, Da a Pa allel Compa ibili y Tool, CUDA,
He e ogeneous compu ing, Rodinia Benchma k Sui e.
5
In el-oneAPI o He e ogeneous Compu ing
Chap e 1: In oduc ion
Nowadays he e ogenei y is widely p esen in bo h high-pe o mance compu ing and
consume elec onics. These sys ems add a mul i ude o co-p ocesso s o accele a o s,
such as GPUs, TPUs, and FPGAs, o he adi ional CPU. Howe e , he e isn' a simple,
po able and efficien me hod o de elop o hese sys ems. In el oneAPI aims o fill his
ole.
This p ojec consis ed on an e alua ion o he Da a Pa allel C++ Compa ibili y Tool
assessing he manual modifica ions needed by he esul ing code and pe o ming hem in
he cases whe e i was assumable, an ins umen aliza ion o he o iginal and he mig a ed
code and he benchma king in diffe en he e ogeneous sys ems. All he code gene a ed,
along wi h he ou pu s o he mig a ion ool and he necessa y makefiles and da ashee s, is
publically a ailable in he gi hub eposi o y:
h ps://gi hub.com/CR-G/In el-oneAPI- o -He e ogeneous-Compu ing
All he p oblems and conce ns encoun e ed du ing he mig a ion we e discussed by email
wi h s aff om In el, con ibu ing o he imp o emen o he Compa ibili y Tool and oneAPI.
This documen consis s on he ollowing 9 chap e s:
●Chap e 1: In oduc ion. Includes a b ie in oduc ion o he e ogeneous sys ems, he
wo k pe o med, a desc ip ion o he s uc u e o his documen and he wo k plan.
●Chap e 2: Mo i a ion and Objec i es. Discusses he mo i a ion behind his p ojec
and i s objec i es.
●Chap e 3: S a e o he A . E olu ion and cu en s a us o he accele a o -based
he e ogeneous compu ing.
●Chap e 4: DPC++. Includes an in oduc ion o Da a Pa allel C++ wi h an example
p og am.
●Chap e 5: DPCT & Rodinia. Desc ibes he Da a Pa allel C++ Compa ibili y Tool and
he Rodinia Benchma k Sui e.
●Chap e 6: Me hodology. Explains he me hodology ollowed by his p ojec ,
including he mig a ion p ocess, he benchma king and he ins umen aliza ion o
he code.
●Chap e 7: Mig a ion Resul s. P esen s he esul s o he mig a ion p ocess,
discussing he necessa y manual in e en ion and he p oblems encoun e ed.
●Chap e 8: Pe o mance Resul s. This chap e exposes he esul s o he
benchma king.
●Chap e 9: Conclusions.
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In el-oneAPI o He e ogeneous Compu ing
Wo k plan
The p ojec was di ided in o h ee phases, a lea ning phase, a mig a ion phase and a
benchma king phase. Du ing he leng h o he p ojec egula mee ings we e held wi h he
u o o moni o he p og ess and discuss esul s. Due o he COVID-19 pandemic, all he
mee ings we e held online ia ideo calls.
Lea ning phase
Du ing his phase I amilia ized mysel wi h DPC++ language and oneAPI wi h he
help o he book Da a Pa allel C++ Mas e ing DPC++ o P og aming o
He e ogeneous Sys ems using C++ and SYCL [11], he examples p o ided by In el
and he ideo eco dings o he Danyso wo kshops abou oneAPI [17] and wi h he
Rodinia Benchma k Sui e, which is widely used and implemen ed in CUDA.
This phase ended wi h he manual mig a ion o he nn benchma k o ensu e all he
necessa y ap i udes we e acqui ed
Mig a ion phase
The DPCT was used o mig a e he Rodinia Benchma k sui e du ing his phase. Also
emails we e exchanged wi h In el ep esen a i es discussing he a ious p oblems
ha appea ed wi h he mig a ion ool.
Benchma king phase
This phase included he modifica ion o he benchma ks o enable he iming o he
execu ion and he benchma king i sel in he Codeplay's docke and he In el
De cloud.
The analysis wi h he N idia Visual P ofile was also pe o med du ing his phase.
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In el-oneAPI o He e ogeneous Compu ing
Chap e 2: Mo i a ion and Objec i es
Mo i a ion
In ecen yea s a clea endency owa ds he e ogenei y in compu ing can be obse ed, no
only in high-pe o mance compu e s, whe e in he op-500 lis N idia GPUs a e he mos
used accele a o s; bu also in desk ops and handheld de ices. Nowadays mos
sma phones include a GPU and he Apple M1 [1] is a sys em on chip, used in he la es
Apple compu e s and able s, ha includes an ARM CPU, a GPU and o he accele a o s like
a 16-co e Neu al Engine o a ificial in elligence applica ions.
These he e ogeneous SOCs, mo e p ominen e e y day, a e clea indica o s o his shi
owa d he e ogenei y. A shi ha makes i impo an o ha e a simple and unified way o
de eloping o diffe en he e ogeneous a chi ec u es wi hou depending on a specific
endo .
Figu e 1: Accele a o sys em sha e o he No embe 2020 Top-500 lis [2]
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In el-oneAPI o He e ogeneous Compu ing
OneAPI simplifies so wa e de elopmen by p o iding he same languages and
p og amming models ac oss accele a o a chi ec u es [8], [5].
FPGAs
FPGAs ha en' seen much adop ion un il he las ew yea s. The eal e olu ion o FPGAs,
and hei adop ion as a he e ogeneous accele a o , came om he eplacemen o he
low-le el Ha dwa e Defini ion Languages used o p og am FPGAs wi h new p og amming
app oaches.
Se e al high-le el op ions, o High Le el Syn hesis (HLS) ools, ha e been de eloped since
he 1990s, howe e , he fi s iable HLS o scien ific pu poses was Al e a's OpenCL SDK
eleased in 2013, ollowed by Xilinx's OpenCL SDKs and HLS ools. Due o he widesp ead
adop ion o GPUs a his ime, he usage o FPGAs as accele a o s became a mo e
p omising idea. In el acqui ed Al e a in 2015 and eb anded i as he SDK as he In el FPGA
SDK o OpenCL. This SDK is s ill ac i e nowadays.
O he p ojec s aimed o make HLS app oaches mo e accessible, usually by adding
so wa e laye s on op o he endo 's HLS backends. Some examples a e he OpenACC
ex ension OpenARC (2016), he OmpSs amewo k ex ended in 2017 o suppo FPGAs and
he ETH Zu ich DaCe amewo k, ha in oduced a con ol-flow g aph and GUI based
in e ace [5].
Fu u e Accele a o s
On op o GPUs and FPGAs, mo e ha dwa e is being explo ed o becoming accele a o s
o he e ogeneous sys ems; like he TPU, a machine lea ning accele a o fi s eleased by
Google in 2018 and quickly adop ed by N idia [5]. F om he same yea , Oak Ridge Na ional
Lab has hos ed an in e na ional con e ence on neu omo phic compu ing, which aims o
emula e he ope a ion and s uc u e o he human b ain. Two examples o neu omo phic
accele a o s a e he IBM T ueNo h and he In el Loihi [5], [19].
Quan um compu ing is also being explo ed o use as he e ogeneous accele a o s by
companies such as D-Wa e and IBM wi h he Q sys em [5].
These a e only some o he accele a o s ha will popula e he wo ld o he e ogeneous
compu ing and mo e a e explo ed e e y yea , p omising a u u e o ex eme he e ogenei y
and ull o challenges o p og amme s [5].
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In el-oneAPI o He e ogeneous Compu ing
Chap e 4: DPC++
DPC++ is he hea o oneAPI. DPC++ p og ams a e w i en in ISO C++ and use he SYCL
pa allel p og amming model o dis ibu e compu a ion ac oss p ocessing elemen s in a
de ice. DPC++ ex ends SYCL wi h ea u es o pe o mance and p oduc i i y.
DPC++ is single sou ce, de ice and hos code can be included in he same sou ce file. A
DPC++ compile gene a es code o bo h he hos and de ice. Any C++ compile can
compile p og ams ha only use he hos subse o DPC++ [9].
Figu e 6: DPC++ C oss-A chi ec u e Compiling [24]
A ypical Da a Pa allel C++ consis s o he ollowing sec ions:
●Asynch onous excep ions om ke nels
●De ice selec o s o diffe en accele a o s
●Buffe s and accesso s (o unified sha ed memo y)
●Queues
●pa allel_ o ke nel
This poin s can be easily explained ollowing he ec o _add [10] example p o ided by in el:
Asynch onous excep ions
Ke nels can un asynch onously and in diffe en s ack ames so e o s can' be p opaga ed
up o he s ack. Fo his and in o de o ca ch asynch onous excep ions, SYCL queues
p o ide e o handle unc ions.
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In el-oneAPI o He e ogeneous Compu ing
s a ic au o excep ion_handle = [ ](cl::sycl::excep ion_lis eLis ) {
o (s d::excep ion_p cons &e : eLis ) {
y {
s d:: e h ow_excep ion(e);
}
ca ch (s d::excep ion cons &e) {
s d:: e mina e();
}
}
};
… …
y {
sycl::queue q(d_selec o , excep ion_handle );
… …
}ca ch (sycl::excep ion cons &e) {
… …
}
De ice Selec o
SYCL and oneAPI p o ide selec o s ha can disco e and p o ide access o he ha dwa e
ha is a ailable on he en i onmen (see Figu e 7). The de aul _selec o selec s he mos
pe o man accele a o a ailable.
// The de aul de ice selec o will selec he mos pe o man de ice.
sycl::de aul _selec o d_selec o ;
Figu e 7: Buil -in de ice selec o s [11]
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In el-oneAPI o He e ogeneous Compu ing
Buffe s and Accesso s
When using buffe s, da a decla ed on he hos is w apped in a buffe and is ans e ed o
he accele a o s implici ly by he DPC++ un ime. The accele a o s ead o w i e o he
buffe h ough an accesso . The un ime also d aws he ke nel dependencies om he
accesso s used, hen dispa ches and uns he ke nels in mos efficien o de .
sycl::buffe a_bu (a_a ay);
sycl::buffe b_bu (b_a ay);
sycl::buffe sum_bu (sum_pa allel.da a(), num_i ems);
… …
q.submi ([&](sycl::handle &h) {
// C ea e an accesso o each buffe wi h access pe mission: ead, w i e, o
// ead/w i e. The accesso is used o access he memo y in he buffe .
sycl::accesso a(a_bu , h, ead_only);
sycl::accesso b(b_bu , h, ead_only);
// The sum_accesso is used o s o e (wi h w i e pe mission) he sum da a.
sycl::accesso sum(sum_bu , h, w i e_only);
… …
});
The h ee access modes o buffe s a e shown in Figu e 8.
Figu e 8: Buffe access modes [11]
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In el-oneAPI o He e ogeneous Compu ing
Unified Sha ed Memo y
Unified Sha ed Memo y (USM) is an al e na i e o buffe s o managing and accessing
memo y om he hos and de ice. Explici da a mo emen wi h USM is accomplished, like
in CUDA, wi h de ice alloca ions and a special memcpy() ound in he queue and handle
classes. Da a can be alloca ed o de ice, hos o bo h (sha ed), see Figu e 9, and i is
copied be ween hos and de ice memo y be o e and a e he ke nel execu es [11] [12].
in * a_de ice = sycl::malloc_de ice<in > num_i ems);
in * b_de ice = sycl::malloc_de ice<in > num_i ems);
in * sum_de ice = sycl::malloc_de ice<in > num_i ems);
q.memcpy(a_de ice, a_a ay, sizeo (in ) * num_i ems).wai ();
q.memcpy(b_de ice, b_a ay, sizeo (in ) * num_i ems).wai ();
… …
// Ke nel execu ion
… …
q.memcpy(sum_a ay, sum_de ice, sizeo (in ) * num_i ems).wai ();
Figu e 9: USM alloca ion ypes [11]
Queue and pa allel_ o
All he con ex and s a es needed o ke nel execu ion a e encapsula ed in a DPC++ queue.
By de aul , a queue is c ea ed and associa ed wi h an accele a o , as indica ed by Figu e
10, h ough a de aul selec o when no pa ame e is passed. I can also ake a specific
de ice selec o and an asynch onous excep ion handle .
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In el-oneAPI o He e ogeneous Compu ing
Figu e 10: A queue is bound o a single de ice [11]
Ke nels a e enqueued o he queue and execu ed. The e a e diffe en ypes o ke nels,
ec o _add uses he basic da a-pa allel pa allel_ o ke nel.
y {
sycl::queue q(d_selec o , excep ion_handle );
… …
q.submi ([&](sycl::handle &h) {
… …
h.pa allel_ o (num_i ems, [=](au o i) { sum[i] = a[i] + b[i]; });
});
}ca ch (sycl::excep ion cons &e) {
… …
}
The ke nel body is he addi ion o wo a ays in he Lambda unc ion. num_i ems, he fi s
pa ame e o h.pa allel_ o specifies he ange o da a he ke nel can p ocess.
When using USM he ke nel call would be:
h.pa allel_ o (num_i ems, [=](au o i) { sum_de ice[i] = a_de ice[i] + b_de ice[i]; });
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In el-oneAPI o He e ogeneous Compu ing
Chap e 5: DPCT & Rodinia
DPC++ Compa ibili y Tool
The In el DPC++ Compa ibili y Tool (DPCT) is a componen o he In el oneAPI Base Toolki
(see Figu e 11) ha assis s he de elope in he mig a ion o a p og am ha is w i en in
CUDA o a p og am w i en in DPC++ [13].
Figu e 11: In el oneAPI Base Toolki [25]
The ool wo ks by in e cep ing he build p ocess and eplacing CUDA code wi h he oneAPI
coun e pa .
Al hough DPCT au oma ically mig a es mos o he code, some manual wo k is equi ed o
a ull mig a ion. The ool ou pu s wa nings o indica e how and whe e manual in e en ion is
needed. These wa nings ha e an assigned ID, o he o m "DPCT10XX", ha can be
consul ed in he De elope Guide and Re e ence. This guide con ains a lis o all he
wa nings, hei desc ip ion and a sugges ion o fix i .
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In el-oneAPI o He e ogeneous Compu ing
Rodinia Benchma ks
Quo ing Rodinia's websi e:
"A ision o he e ogeneous compu e sys ems ha inco po a e di e se accele a o s
and au oma ically selec he bes compu a ional uni o a pa icula ask is widely
sha ed among esea che s and many indus y analys s; howe e , he e a e no
ag eed-upon benchma ks o suppo he esea ch needed in he de elopmen o
such a pla o m. The e a e many sui es o pa allel compu ing on gene al-pu pose
CPU a chi ec u es, bu accele a o s all in o a gap ha is no co e ed by p e ious
benchma k de elopmen . Rodinia is eleased o add ess his conce n." [14].
The Rodinia Benchma k Sui e is implemen ed in CUDA, OpenMP and OpenCL and includes
he ollowing applica ions:
Applica ion
Dwa es
Domain
Implemen a ions
Leukocy e
S uc u ed G id
Medical Imaging
CUDA, OMP, OCL
Hea Wall
S uc u ed G id
Medical Imaging
CUDA, OMP, OCL
MUMme GPU
G aph T a e sal
Bioin o ma ics
CUDA, OMP
CFD Sol e
Uns uc u ed G id
Fluid Dynamics
CUDA, OMP, OCL
LU Decomposi ion
Dense Linea Algeb a
Linea Algeb a
CUDA, OMP, OCL
Ho Spo
S uc u ed G id
Physics Simula ion
CUDA, OMP, OCL
Back P opaga ion
Uns uc u ed G id
Pa e n Recogni ion
CUDA, OMP, OCL
Needleman-Wunsch
Dynamic
P og amming
Bioin o ma ics
CUDA, OMP, OCL
Kmeans
Dense Linea Algeb a
Da a Mining
CUDA, OMP, OCL
B ead h-Fi s Sea ch
G aph T a e sal
G aph Algo i hms
CUDA, OMP, OCL
SRAD
S uc u ed G id
Image P ocessing
CUDA, OMP, OCL
S eamclus e
Dense Linea Algeb a
Da a Mining
CUDA, OMP, OCL
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In el-oneAPI o He e ogeneous Compu ing
Pa icle Fil e
S uc u ed G id
Medical Imaging
CUDA, OMP, OCL
Pa hFinde
Dynamic
P og amming
G id T a e sal
CUDA, OMP, OCL
Gaussian Elimina ion
Dense Linea Algeb a
Linea Algeb a
CUDA, OCL
k-Nea es Neighbo s
Dense Linea Algeb a
Da a Mining
CUDA, OMP, OCL
La aMD2
N-Body
Molecula Dynamics
CUDA, OMP, OCL
Myocy e
S uc u ed G id
Biological Simula ion
CUDA, OMP, OCL
B+ T ee
G aph T a e sal
Sea ch
CUDA, OMP, OCL
GPUDWT
Spec al Me hod
Image/Video
Comp ession
CUDA, OCL
Hyb id So
So ing
So ing Algo i hms
CUDA, OCL
Ho spo 3D
S uc u ed G id
Physics Simula ion
CUDA, OMP, OCL
Huffman
Fini e S a e Machine
Lossless da a
comp ession
CUDA, OCL
Table 1: Rodinia 3.1 applica ions [14]
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In el-oneAPI o He e ogeneous Compu ing
Chap e 6: Me hodology
The wo kflow, isualized in Figu e 12, was di ided in o wo main p ocesses: he mig a ion
p ocess and he benchma king p ocess.
Figu e 12: Wo kflow
Mig a ion p ocess
In o de o mig a e he Rodinia benchma ks o CUDA o DPC++ he ollowing s eps
we e ollowed:
1. Gene a e a compila ion da abase wi h he ool in e cep -build.
This c ea es a json file wi h all he compile in oca ions and s o es he names
o he inpu files and he compile op ions.
This is done wi h he command in e cep -build make.
2. Use he In el DPC++ Compa ibili y Tool o mig a e he code.
The command
dpc -p compile_commands.json --in- oo =. --ou - oo =mig a ion
mig a es he files in he cu en di ec o y and s o es he esul in he
mig a ion olde .
Du ing his s ep commen s a e inse ed whe e he ool couldn' mig a e he
code o whe e he use should e iew he mig a ion.
3. Ve i y he mig a ion and add ess any DPCT wa nings gene a ed. Consul he
Diagnos ics Re e ence [18] o de ailed in o ma ion abou he DPCT
wa nings.
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In el-oneAPI o He e ogeneous Compu ing
A e analyzing he esul s o hese measu emen s, he benchma ks ha had he wo s
pe o mance compa ed o he o iginal CUDA applica ion ecei ed a mo e in-dep h analysis
using he N idia Visual P ofile [21].
Figu e 16: Wo kflow (CUDA s oneAPI)
P ofiling
On op o he execu ion o he ins umen alized code, he mos ele an applica ions o he
Rodinia benchma ks we e analysed using he N idia Visual P ofile , a pe o mance p ofiling
ool p o ided by N idia.
Figu e 17: Example o he N idia Visual P ofile [21]
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In el-oneAPI o He e ogeneous Compu ing
This ool allows pe o ming a low-le el analysis o he code, showing de ails abou he
ke nels and he memo y ans e no isible by o he means.
O he a chi ec u es
Taking ad an age o he po abili y p o ided by oneAPI, he benchma ks we e also
execu ed in he In el De cloud, wi h wo In el XeonGold6128 CPUs and an In el
UHDG aphicsP630 GPU as de ices.
The In el De cloud allows i s use s o execu e applica ions wi h diffe en ha dwa e
en i onmen s ha include a ious In el CPUs, GPUs and FPGAs.
Figu e 18: Wo kflow (benchma king)
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In el-oneAPI o He e ogeneous Compu ing
Chap e 7: Mig a ion Resul s
Du ing he mig a ion p ocess he DPC++ Compa ibili y Tool gene a ed a se ies o wa nings
indica ing possible p oblems and he need o manual in e en ion by he use . These a e
discussed in he ollowing sec ions.
Wa nings
Ac oss all he benchma ks 99 files we e p ocessed by he DPC++ Compa ibili y Tool, wi h a
o al o 43485 lines o code.
I ga e a o al o 461 wa nings, wi h an a e age o 4.65 wa nings pe file o a wa ning e e y
94.3 lines.
Wa ning code
Numbe o appea ances
DPCT1000
4
DPCT1001
4
DPCT1003
171
DPCT1004
1
DPCT1005
15
DPCT1009
45
DPCT1010
38
DPCT1012
20
DPCT1019
1
DPCT1022
2
DPCT1024
2
DPCT1026
8
DPCT1027
2
DPCT1035
9
DPCT1039
7
DPCT1049
75
33
In el-oneAPI o He e ogeneous Compu ing
DPCT1051
2
DPCT1059
14
DPCT1064
2
DPCT1065
29
DPCT1072
1
DPCT1077
9
To al
461
Table 3: Wa nings gi en by DPCT
See he In el DPC++ Compa ibili y Tool De elope Guide and Re e ence [18] o mo e
in o ma ion abou hese wa nings.
These wa nings can be g ouped in he ollowing ca ego ies:
●E o handling ela ed wa nings:
DPCT1000, DPCT1001, DPCT1003, DPCT1009, DPCT1010, DPCT1024.
To al: 264 - 57.3%
●De ice in o ma ion ela ed wa nings:
DPCT1005, DPCT1019, DPCT1022, DPCT1051, DPCT1072.
To al: 21 - 4.6%
●Ke nel in oca ion wa nings:
DPCT1049.
To al: 75 - 16.3%
●Time measu emen wa nings:
DPCT1012.
To al: 20 - 4.3%
●Wa nings caused by he emo al o unnecessa y unc ion calls:
DPCT1026, DPCT1027.
To al 10 - 2.1%
●Wa ning gene a ed because SYCL no suppo s some hing:
DPCT1059.
To al 14 - 3%
34
In el-oneAPI o He e ogeneous Compu ing
●Pe o mance imp o ing sugges ions:
DPCT1065.
To al 29 - 6.3%
●Mac o ela ed wa nings:
DPCT1064, DPCT1077.
To al 11 - 2.4%
●O he :
DPCT1004, DPCT1035, DPCT1039
To al 17 - 3.7%
Figu e 19: Dis ibu ion o he wa nings gene a ed by DPCT
Mos o he wa nings gene a ed by he compa ibili y ool (57.3%) a e caused by he ac
ha SYCL uses excep ions ins ead o e o codes. Al hough i migh be desi able in o de o
handle any e o ha migh occu in un ime, no manual modifica ions we e manda o y o
hese wa nings as he ool modifies all e o checks so hey always e u n a success.
The second g oup o wa nings appea in e e y ke nel in oca ion and simply eminds he
use he ac ha he a ge ed de ice migh ha e a smalle limi o he wo kg oup size. This
is usually he case when compa ing an N idia GPU wi h an in eg a ed In el GPU.
O he es i should be no ed ha he wa nings ela ed wi h mac os and de ice in o ma ion
a e he ones ha equi e he mos manual in e en ion om he use .
35
In el-oneAPI o He e ogeneous Compu ing
I is wo h men ioning he ac ha , as he mig a ed code is a benchma k, he amoun o
ime measu emen ela ed wa nings is much bigge han i would be in o he codes.
In he end wen y ou o he wen y h ee benchma ks we e success ully mig a ed wi hou
majo manual in e en ion, esul ing in a success a e o almos 87%. In he cases whe e
he mig a ion wasn' success ul i was due o issues known by In el. Wo k is being done o
sol e hese issues and a fix is planned in he nex upda e (oneAPI 2021.3) o some o hem.
Benchma k
Success ul mig a ion
b+ ee
✓
backd op
✓
b s
✓
c d
✓
dw 2d
✓
gaussian
✓
hea wall
✓
ho spo
✓
ho spo 3D
✓
huffman
✓
hyb idso
X
kmeans
X
la aMD
✓
leukocy e
✓
lud
✓
mumme gpu
X
myocy e
✓
nn
✓
nw
✓
pa iclefil e
✓
pa hfinde
✓
s ad
✓
s eamclus e
✓
Table 4: Mig a ion successes
36

In el-oneAPI o He e ogeneous Compu ing
Manual modifica ions
A e he au oma ic mig a ion some manual modifica ions o he code we e
necessa y, always add essing he wa ning messages gene a ed by he ool. As a
summa y, we can illus a e in he ollowing lines he main modifica ions pe o med:
●The wo kg oup size migh need o be adjus ed depending on he de ice used:
DPCT sugges s que ying in o::de ice::max_wo k_g oup_sice o ge he
de ice limi and adjus he wo kg oup size acco dingly.
●When he block size is specified wi h a mac o and used o c ea e a sycl:: ange he
expanded alue should be changed back o he mac o. When his is he case he
ool lea es he o iginal mac o commen ed.
Fo example:
q_c 1.submi ([&](sycl::handle &cgh) {
sycl:: ange<2>weigh _ma ix_ ange_c 1(16 /*HEIGHT*/,16 /*WIDTH*/);
...
}
should be eplaced wi h
q_c 1.submi ([&](sycl::handle &cgh) {
sycl:: ange<2>weigh _ma ix_ ange_c 1(HEIGHT
,WIDTH);
...
}
●As SYCL uses excep ions ins ead o e o codes e e y check is modified by he ool
o always succeed. P ope e o checking migh be added manually wi h y-ca ch
cons uc ions as i is de ailed below:
A sou ce code line like
check_e o (cudaMalloc(( oid **) &a ayX_GPU, sizeo (double)*Npa icles));
will be mig a ed o
check_e o ((a ayX_GPU =sycl::malloc_de ice<double>(Npa icles,q_c 1), 0));
In o de o handle any possible un ime e o his should be changed o some hing
like
y{
a ayX_GPU =sycl::malloc_de ice<double>(Npa icles,
q_c 1);
ca ch (sycl::excep ion cons &e) {
Handle excep ion
}
37
In el-oneAPI o He e ogeneous Compu ing
●The de ice selec ion logic mus be manually e iewed as all DPC++ de ices (no
only he GPU) can be used o submi asks. I is impo an o ake his in o accoun
when he d i e e sion is used o de ec a GPU in he o iginal CUDA sou ce.
i (de P op.ge _majo _ e sion() < 1) { … }
used in he o iginal CUDA code o de ec he p esence o a GPU can be eplaced by
i (!dpc ::ge _cu en _de ice().is_gpu()){ … }
In his example he execu ion finished when no GPU was a ailable, bu i has no
sense on DPC++ as i allows o un he de ice code in o o he de ices, such as
CPU. In his case he check was modified so i con inues he execu ion in ano he
de ice i no GPU is a ailable.
●Many CUDA de ice p ope ies don' ha e a SYCL equi alen , a e sligh ly diffe en o
a en' cu en ly suppo ed. This will cause in many occasions he e ie al o
inco ec alues. Fo his eason he use mus manually e iew and co ec he
in o ma ion que ies o he de ice.
●I he ool makes some assump ion o gene a e he DPC++ code, i will place a
wa ning ins uc ing he use o e iew he modified code.
Fo example DPCT1039:
"The In el® DPC++ Compa ibili y Tool deduces whe he he fi s pa ame e o an
a omic unc ion poin s o a global memo y add ess space o a local memo y
space, using he las assignmen ’s alue o he fi s pa ame e o he a omic
unc ion..."
●SYCL only suppo s 4-channel image o ma so he code needs o be manually
adjus ed. An example o he needed modifica ions is gi en in he In el DPC++
Compa ibili y Tool De elope Guide and Re e ence [18].
●When a unc ion call is used in a mac o defini ion i migh need o be mig a ed
diffe en ly depending on how he mac o is called. All uses o his mac o mus be
e iewed.
●Inside a ke nel, DPCT sugges s eplacing ba ie () wi h ba ie (sycl::access::
ence_space::local_space) o be e pe o mance i he e is no access o global
memo y. In his case he use should check he memo y accesses and he
modifica ion.
●I a mac o edefines a s anda d SYCL ype i may cause conflic s. The de elope
guide and e e ence sugges s he use o ename he mac o.
38
In el-oneAPI o He e ogeneous Compu ing
P oblems encoun e ed
●CL_INVALID_IMAGE_SIZE: In e e y benchma k whe e an image da a ype is used
he execu ion ends wi h an excep ion (CL_INVALID_IMAGE_SIZE). This is a known
issue ha occu s when he in o::de ice::image2d_max_wid h alue o he de ice is
less han he wid h o he image passed in o he ke nel. A e discussing his wi h
some In el's s aff a wo ka ound was sugges ed o CPU. The e is no solu ion o
GPU ye .
●When a unc ion is called inside a complex mac o some imes he ool e oneously
eplaces he pa ame e s o he unc ion called wi h names om an in oca ion u he
down he code.
#define BIND_TEX_ARRAY( ex,a ,desc)do {
CUDA_SAFE_CALL(cudaBindTex u eToA ay( ex, a , desc));
++num_bind_ ex_calls;
}while(0)
was mig a ed o
#define BIND_TEX_ARRAY( ex,a ,desc)do {
CUDA_SAFE_CALL((BIND_TEX_ARRAY(node ex,
(cudaA ay*) e ->d_node_ ex_a ay,
nodeTex u eDesc).a ach(BIND_TEX_ARRAY(node ex,
(cudaA ay*) e ->d_node_ ex_a ay,nodeTex u eDesc),
BIND_TEX_ARRAY(node ex,
(cudaA ay*) e ->d_node_ ex_a ay, nodeTex u eDesc)),
0));
++num_bind_ ex_calls;
}while(0)
This is a known bug and a fix is planned o upda e 2021.3
●The la es CUDA suppo ed e sion is 11.1. This causes small p oblems wi h he
in e cep -build ool as i won' find some lib a ies. Re-execu ing he command wi h
--append esumes he execu ion om he e o , effec i ely fixing he p oblem.
39
In el-oneAPI o He e ogeneous Compu ing
●Lea ing some posi ions o an a ay unini ialized migh esul in a segmen a ion aul .
This occu ed in he pa iclefil e benchma k whe e he unc ion
oid s elDisk(in * disk,in adius){
in diame e = adius*2-1;
in x,y;
o (x=0;x<diame e ;x++){
o (y=0;y<diame e ;y++){
double dis ance =
sq (pow((double)(x- adius +1), 2) +
pow((double)(y- adius +1), 2));
i (dis ance < adius)
disk[x*diame e +y] = 1;
}
}
}
le a posi ion unini ialized when he dis ance was g ea e o equal o he adius.
The o iginal CUDA e sion an wi hou any p oblem, bu his caused he men ioned
segmen a ion aul in DPC++. The solu ion was se ing o 0 he unini ialised memo y
posi ions.
40
In el-oneAPI o He e ogeneous Compu ing
Figu e 25: dw 2d (oneAPI) la ency analysis
47

In el-oneAPI o He e ogeneous Compu ing
O e all pe o mance
In el oneAPI has he added ad an age o no being es ic ed o one endo like CUDA. Fo
his eason he benchma ks we e also es ed in he In el De cloud using a pai o In el
XeonGold6128 CPU and an in eg a ed In el UHDG aphicsP630 GPU as de ices.
As seen in Figu e 26, al hough, as expec ed, he dedica ed N idia GPU ou pe o med he
CPU and he in eg a ed GPU in almos e e y case, he e a e ins ances whe e he CPU
and/o he in eg a ed GPU ma ched o e en ou pe o med he N idia GPU. This was he
case when he applica ion didn' ake ad an age o he massi e pa alleliza ion capabili ies
o a GPU o he o e head caused by he mo emen o memo y be ween he hos and he
de ice wasn' jus ified by he speedup p o ided by he accele a o .
Figu e 26: To al execu ion imes ac oss all es ed de ices (loga i hmic scale)
Con inuing wi h he example o nn ha calcula es he euclidean dis ance be ween a se o
poin s, he execu ion was much as e in he dedica ed GPU due o use o sq () and he
high pa alleliza ion o he ke nel. The in eg a ed GPU akes ad an age o his pa alleliza ion,
hus ou pe o ming he CPUs, bu lacks he special compu e uni s ha he dedica ed GPU
has o calcula ing squa e oo s.
By he o he hand, he myocy e es is a clea example o a case whe e he speedup
p o ided by he GPU does no jus i y he o e head in oduced by he memo y ans e . In
his case he in eg a ed GPU akes ad an age o he educed la ency ha p o ides being in
he same chip as he hos and ou pe o ms he dedica ed GPU, bu he as e and mo e
complex co es o he CPUs gi es hem he ad an age in his case whe e he massi e
pa alleliza ion capabili ies o he GPUs a e no ully u ilized.
48
In el-oneAPI o He e ogeneous Compu ing
Chap e 9: Conclusions
As s a ed in chap e s 2 and 3, he e is a clea endency owa ds he e ogenei y and, in
ecen yea s, many me hods o p og amming hese he e ogeneous sys ems ha e appea ed
wi h g ea e o lesse success.
OneAPI aims o p o ide a simple and unified p og amming me hod o all hese diffe en
he e ogeneous sys ems, independen ly o he accele a o used o i 's endo , allowing high
and low le el app oaches acili a ing he p og amme 's wo k in his highly he e ogeneous
wo ld we a e mo ing owa ds.
The wo k done mig a ing, benchma king and p ofiling he Rodinia Benchma k sui e shows
p omising esul s:
●Al hough some wo k emains o be done, he Da a Pa allel C++ Compa ibili y Tool
g ea ly s eamlines he mig a ion p ocess om CUDA o oneAPI. Twen y ou o he
wen y h ee benchma ks we e success ully mig a ed wi hou majo manual
in e en ion, esul ing in a success a e o almos 87% and allowing p e iously
N idia specific code o un in o he accele a o s.
●Mos o he p oblems encoun e ed du ing he mig a ion we e caused by known bugs
ha will be fixed o e ime. These bugs we e he main eason why he mig a ion
ailed in hyb idso , kmeans and mumme gpu.
●The pe o mance o he esul ing mig a ed code is, in many cases, compa able o
he o iginal CUDA sou ce e en wi hou applying any op imiza ion. Backp op,
gaussian and s eamclus e achie e a pe o mance diffe ence o 1% o less and b s,
eule 3D_double, la aMD, lud and pa hfinde keep he o e head unde 17%.
●Rega ding he basic memo y ope a ions, de ice memo y alloca ion, copy memo y
hos o de ice, copy memo y de ice o hos and de ice memo y ee, he
pe o mance is equi alen and any o e head de ec ed a ound hese ope a ions is
caused by o he ins uc ions in oduced by oneAPI.
●In he cases whe e he pe o mance loss is mo e significan i is due o ei he poo
memo y and egis e usage o insufficien op imiza ion o he compiled code. Bo h
hese p oblems should be sol ed, o a leas mi iga ed, by a mo e ma u e and
ad anced compile .
49
In el-oneAPI o He e ogeneous Compu ing
E en wi h he pe o mance loss, he capabili y o execu ing he ke nels in a mul i ude o
diffe en de ices, no only N idia GPUs, is a g ea ad an age o e CUDA ha jus ifies he
effo pu on he mig a ion o , a leas , makes i wo h conside ing i . I is also wo h no icing
ha oneAPI wi h he In el XeonGold6128 CPUs achie ed simila pe o mance o he o iginal
CUDA e sion o pa iclefil e _nai e and su passed i in eule 3D_double, myocy e and
pa iclefil e _floa .
Bo h, oneAPI and DPCT, a e in ac i e de elopmen . The esul s o his p ojec we e
discussed wi h In el's s aff and mos o he ound p oblems and bugs we e known by In el;
some fixes a e e en planned o he nex upda e and u he op imiza ions and compile
upg ades migh educe he obse ed pe o mance losses.
All o his eaffi ms he belie ha oneAPI and SYCL will become a u u e s anda d o
he e ogeneous p og amming.
50
In el-oneAPI o He e ogeneous Compu ing
Bibliog aphy
[1] "Apple M1 - Wikipedia" [Online]. A ailable:
h ps://en.wikipedia.o g/wiki/Apple_M1
[2] "Lis S a is ics | TOP500" [Online]. A ailable:
h ps://www. op500.o g/s a is ics/lis
[3] "De elopmen o e Time | TOP500" [Online]. A ailable:
h ps://www. op500.o g/s a is ics/o e ime
[4] "CUDA Zone | NVIDIA De elope " [Online]. A ailable:
h ps://de elope .n idia.com/cuda-zone
[5] Jacob Lambe , "E olu ion o P og amming App oaches o High-Pe o mance
He e ogeneous Sys ems", Compu e Science Uni e si y o O egon, Uni ed S a es,
Decembe 14, 2020. A ailable:
h ps://www.cs.uo egon.edu/Repo s/AREA-202012-Lambe .pd
[6] P adeep Gup a, "CUDA Re eshe : The CUDA P og amming Model | N idia
De elope Blog" [Online]. A ailable:
h ps://de elope .n idia.com/blog/cuda- e eshe -cuda-p og amming-model
[7] "SYCL O e iew - The Kh onos G oup Inc" [Online]. A ailable:
h ps://www.kh onos.o g/sycl/
[8] "Welcome o oneAPI - oneAPI Documen a ion" [Online]. A ailable:
h ps://docs.oneapi.com/ e sions/la es /index.h ml
[9] "DPC++ Re e ence - DPC++ Re e ence Documen a ion" [Online]. A ailable:
h ps://docs.oneapi.com/ e sions/la es /dpcpp/index.h ml#da a-pa allel-c-dpc
[10] "DPC++ Founda ions Code Sample" [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/a icles/dpcpp- ounda ions-
code-sample.h ml
[11] James Reinde s, e al., "Da a Pa allel C++ Mas e ing DPC++ o P og amming
o He e ogeneous Sys ems using C++ and SYCL" A ailable:
h ps://link.sp inge .com/book/10.1007%2F978-1-4842-5574-2
51
In el-oneAPI o He e ogeneous Compu ing
[12] "Da a Pa allel C++ USM Code Samples" [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/a icles/dpcpp-usm-code-sa
mple.h ml
[13] "Ge S a ed wi h he In el DPC++ Compa ibili y Tool" [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/documen a ion/ge -s a ed-
wi h-in el-dpcpp-compa ibili y- ool/ op.h ml
[14] "s a [Rodinia]" [Online]. A ailable:
h p:// odinia.cs. i ginia.edu/doku.php
[15] "In el DPC++ Compa ibili y Tool" [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/ ools/oneapi/componen s/dp
c-compa ibili y- ool.h ml
[16] "Ruyk/dpcpp-cuda-examples-docke " [Online]. A ailable:
h ps://gi hub.com/Ruyk/dpcpp-cuda-examples-docke
[17] "Encuen o Online Desa ollado es In el So wa e" [Online]. A ailable:
h ps://www.danyso .com/encuen o-online-desa ollado es-in el-so wa e
[18] "Diagnos ics Re e ence" [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/documen a ion/in el-dpcpp-
compa ibili y- ool-use -guide/ op/diagnos ics- e e ence.h ml
[19] "Neu omo phic Compu ing - Nex Gene a ion o AI" [Online]. A ailable:
h ps://www.in el.com/con en /www/us/en/ esea ch/neu omo phic-compu ing.h ml
[20] "Pandemic dis o s global GPU ma ke esul s | Jon Peddie Resea ch" [Online].
A ailable:
h ps://www.jonpeddie.com/p ess- eleases/pandemic-dis o s-global-gpu-ma ke - e
sul s
[21] "NVIDIA Visual P ofile | NVIDIA De elope " [Online]. A ailable:
h ps://de elope .n idia.com/n idia- isual-p ofile
[22] "In el oneAPI P og amming Guide - Glossa y" [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/documen a ion/oneapi-p og
amming-guide/ op/glossa y.h ml
[23] "Th ead block (CUDA p og amming) - Wikipedia" [Online]. A ailable:
h ps://en.wikipedia.o g/wiki/Th ead_block_%28CUDA_p og amming%29
52

In el-oneAPI o He e ogeneous Compu ing
[24] "In el oneAPI DPC++/C++ Compile - Da a Pa allel C++ o C oss-A chi ec u e
Applica ions" [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/ ools/oneapi/componen s/dp
c-compile .h ml
[25] "In el oneAPI Base Toolki o C oss-A chi ec u e De elopmen " [Online]. A ailable:
h ps://so wa e.in el.com/con en /www/us/en/de elop/ ools/oneapi/base- oolki .h
ml
[26] "CUDA Bina y U ili ies :: CUDA Toolki Documen a ion" [Online]. A ailable:
h ps://docs.n idia.com/cuda/cuda-bina y-u ili ies/index.h ml#ins uc ion-se - e
53
In el-oneAPI o He e ogeneous Compu ing
Glossa y
Accele a o :Specialized componen con aining compu e esou ces ha can quickly
execu e a subse o ope a ions. Examples include CPU, FPGA, GPU [22].
Accesso : Communica es he desi ed loca ion (hos , de ice) and mode ( ead, w i e) o
access [22].
Buffe : Memo y objec ha communica es he ype and numbe o i ems o ha ype o be
communica ed o he de ice o compu a ion [22].
Compu e uni :A g ouping o p ocessing elemen s in o a ‘co e’ ha con ains sha ed
elemen s o use be ween he p ocessing elemen s and wi h as e access han memo y
esiding on o he compu e uni s on he de ice [22].
De ice:An accele a o o specialized componen con aining compu e esou ces ha can
quickly execu e a subse o ope a ions. A CPU can be employed as a de ice, bu when i is,
i is being employed as an accele a o . Examples include CPU, FPGA, GPU [22].
FPGA: Field-p og ammable ga e a ay. I is an in eg a ed ci cui designed o be configu ed
a e manu ac u ing.
GPU: G aphics p ocessing uni .
Ke nel:Code ha execu es on he de ice [22].
P ocessing elemen :Indi idual engine o compu a ion ha makes up a compu e uni [22].
Sha ed memo y: Special memo y egion ha can be accessed by all h eads in he same
g oup.
SIMD: Single ins uc ion mul iple da a.
SOC: Sys em on Chip.
TPU: Tenso P ocessing Uni . I is an AI accele a o o neu al ne wo k machine lea ning.
Wa p: A wa p is a se o h eads wi hin a h ead block such ha all he h eads in a wa p
execu e he same ins uc ion [23].
Wo kg oup:Collec ion o wo k-i ems ha execu e on a compu e uni [22].
Wo k-i em: Basic uni o compu a ion in he oneAPI p og amming model. I is associa ed
wi h a ke nel which execu es on he p ocessing elemen [22].
54