High Performance Computing

695 Pages·2017·47.247 MB·English

by  Thomas Sterling, Matthew Anderson and Maciej Brodowicz

High Performance
Computing
Modern Systems and Practices
Thomas Sterling
Matthew Anderson
Maciej Brodowicz
School of Informatics, Computing, and Engineering
Indiana University, Bloomington
Foreword by C. Gordon Bell
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Foreword
High Performance Computing is a needed follow-on to Becker and Sterling’s 1994 creation of the
Beowulfclustersrecipetobuildscalablehighperformancecomputers(alsoknownasasupercomputers)
from commodity hardware. Beowulf enabled groups everywhere to build their own supercomputers.
NowwithhundredsofBeowulfclustersoperatingworldwide,thiscomprehensivetextaddressesthecrit-
ical missing link of an academic course for training domain scientists and engineersdand especially
computer scientists. Competence involves knowing exactly how to create and run (e.g., controlling,
debugging, monitoring, visualizing, evolving) parallel programs on the congeries of computational
elements(cores)thatconstitutetoday’ssupercomputers.
Masteryoftheseever-increasing,scalable,parallelcomputingmachinesgivesentryintoacompar-
ativelysmallbutgrowingelite,andistheauthors’goalforreadersofthebook.Lestthereaderbelieves
the name is unimportant: the first conference in 1988 was the ACM/IEEE Supercomputing Confer-
ence, also known as Supercomputing 88; in 2006 the name evolved to the International Conference
on High Performance Computing, Networking, Storage, and Analysis, abbreviated SCXX. About
11,000 peopleattended SC16.
Itishardtodescribea“supercomputer,”butIknowonewhenIseeone.Personally,Ineverpassup
a visit to a supercomputer having seen the first one in 1961dthe UNIVAC LARC (Livermore
Advanced Research Computer) at Lawrence Livermore National Laboratory, specified by Edward
Tellertorunhydrodynamicsimulationsfornuclearweaponsdesign.LARCconsistedofafewdozen
cabinetsofdenselypackedcircuitboardinterconnectedwithafewthousandmilesofwiresandafew
computationalunitsoperatingata100kHzrate.In2016thelargestSunwayLightsupercomputerin
ChinaoperatedatrilliontimesfasterthanLARC.Itconsistsofover10millionprocessingcoresoper-
ating at a 1.5GHz rate, and consumes 15MW. The computer is housed in four rows of 40 cabinets,
containing256processingnodes.Anodehasfourinterconnected8MBprocessors,controlling64pro-
cessingelementsorcores.Thusthe10.6millionprocessingelementsdeliver125peakpetaflops,i.e.,
160cabinets(cid:1)256physicalnodes(cid:1)4computers(cid:1)(1controlþ8(cid:1)8)processingelementsorcores
with a 1.31PB memory (160(cid:1)256(cid:1)4(cid:1)8GB). Several of the Top 500 supercomputers have
O(10,000) computing nodes that connect and control graphic processing units (GPUs) with O(100)
cores. Today’s challenge for computational program developers is designing the architecture and
implementationof programsto utilize these megaprocessor computers.
From a user perspective, the “ideal high performance computer” has an infinitely fast clock,
executes a single instruction stream program operating on data stored in an infinitely large and fast
single-memory, and comes in any size to fit any budget or problem. In 1957 Backus established the
von Neumann programming model with Fortran. The first or “Cray” era of supercomputing from
the 1960s through the early 1990s sawthe evolutionof hardware to support this simple, easy-to-use
idealbyincreasingprocessorspeed,pipelininganinstructionstream,processingvectorswithasingle
instruction,andfinallyaddingprocessorsforaprogramheldinthesingle-memorycomputer.Bythe
early1990sevolutionofasinglecomputertowardtheidealhadstopped:clockspeedsreachedafew
GHz,andthenumberofprocessorsaccessingasinglememorythroughinterconnectionwaslimitedto
a few dozen. Still, the limited-scale, multiple-processor shared memory is likely to be the most
straightforward toprogram and use!
xix
xx FOREWORD
Fortunately,inthemid-1980sthe“killermicroprocessor”arrived,demonstratingcosteffectiveness
and unlimited scaling just by interconnecting increasingly powerful computers. Unfortunately, this
multicomputererahasrequiredabandoningboththesinglememoryandthesinglesequentialprogram
idealofFortran.Thus“supercomputing”hasevolvedfromahardwareengineeringdesignchallengeof
the single (mono-memory) computer of the Seymour Cray era (1960e95) to a software engineering
designchallengeofcreatingaprogramtoruneffectivelyusingmulticomputers.Programsfirstoper-
ated on 64 processing elements (1983), then 1000 elements (1987), and now 10million (2016) pro-
cessing elements in thousands of fully distributed (mono-memory) computers in today’s
multicomputerera.Soineffect,today’shighperformancecomputing(HPC)nodesarelikethesuper-
computersofadecadeago,asprocessingelementshavegrown36%peryearfrom1000computersin
1987to 10million processing elements (contained in100,000 computernodes).
HighPerformanceComputingistheessentialguideandreferenceformasteringsupercomputing,
as the authors enumerate the complexity and subtleties of structuring for parallelism, creating, and
running these large parallel and distributed programs. For example, the largest climate models
simulateocean,ice,atmosphere,andlandconcurrentlycreatedbyateamofadozenormoredomain
scientists, computational mathematicians, and computerscientists.
Programcreationincludesunderstandingthestructureofthecollectionofprocessingresourcesand
theirinteractionfordifferentcomputers,frommultiprocessorstomulticomputers(Chapters2and3),
andthevariousoverallstrategiesforparallelization(Chapter9).Othertopicsincludesynchronization
andmessage-passingcommunicationamongthepartsofparallelprograms(Chapters7and8),addi-
tional libraries that form a program (Chapter 10), file systems (Chapter 18), long-term mass storage
(Chapter17),andcomponentsforthevisualizationofresults(Chapter12).Standardbenchmarksfor
asystemgiveanindicationofhowwellyourparallelprogramislikelytorun(Chapter4).Chapters16
and17introduceanddescribethetechniquesforcontrollingacceleratorsandspecialhardwarecores,
especiallyGPUs,attachedtonodestoprovideanextratwoordersofmagnitudemoreprocessingper
node.TheseattachmentsareanalternativetothevectorprocessingunitsoftheCrayera,andtypified
by the Compute Unified Device Architecture, or CUDA, model and standard to encapsulate
parallelism acrossdifferent accelerators.
Unlike the creation, debugging, and execution of programs that run interactively on a personal
computer,smartphone,orwithinabrowser,supercomputerprogramsaresubmittedviabatchprocess-
ingcontrol.Runningaprogramrequiresspecifyingtothecomputertheresourcesandconditionsfor
controlling your program with batch control languages and commands (Chapter 5), getting the pro-
gramintoareliableanddependablestatethroughdebugging(Chapter14),checkpointing,i.e.,saving
intermediateresultsonatimelybasisasinsuranceforthecomputationalinvestment(Chapter20),and
evolvingandenhancinga program’s efficacythroughperformance monitoring (Chapter 13).
Chapter21concludeswithaforwardlookattheproblemsandalternativesformovingsupercom-
putersandtheabilitytousethemtopetascaleandbeyond.Infact,theonlypartofHPCnotdescribed
in this book is the incredible teamwork and evolution of team sizes for writing and managing HPC
codes. However, the most critical aspect of teamwork resides with the competence of the individual
members. This book is yourguide.
Gordon Bell
October2017
Preface
THE PURPOSE OF THIS TEXTBOOK
Highperformancecomputing(HPC)isamultidisciplinaryfieldcombininghardwaretechnologiesand
architecture,operatingsystems,programmingtools,software,andend-userproblemsandalgorithms.
Acquiring the necessary concepts, knowledge, and skills for capable engagement within HPC
routinelyinvolvesanapprenticeshipatoneofafewrarefiedsiteswiththeessentialexperts,facilities,
andmissionobjectives.Whetherone’sgoalsareassociatedwithspecificend-userdomainssuchassci-
ence,engineering,medicine,orcommercialapplications,orfocusedontheenablingsystems’technol-
ogies and methodologies that make supercomputing effective, the entry-level practitioner must
embraceawiderangeofdistinctbutinterrelatedandinterdependentareasthatrequireanunderstand-
ing of their synergies to yield the necessary expertise. The study material could easily encompass a
dozenormorebooksandmanuals,buteventogethertheywouldnotdeliverthenecessaryperspective
thatfullyembodiesthefieldasawholeandguidesthestudentinpursuitofaneffectivepathtoachieve
sufficient expertise.
Thistextbookisdesignedtobridgethegapbetweenmyriadsourcesofnarrowfocusandtheneed
forasinglesourcethatspansandinterconnectstherangeofdisciplinescomprisingtheHPCfield.Itis
anentry-leveltextrequiringaminimumofprerequisites,butprovidesafullunderstandingofthedo-
mainsandtheirmutualeffectsthatmakesupercomputinganinterdisciplinaryfield.Fromapractical
point of view, this textbook builds valuable and specific skill-sets for parallel programming, debug-
ging,performancemonitoring,systemresourceusageandtools,andresultvisualizationamongother
usefultechniques.Theseskillsareprovidedinthereinforcingcontextofbasicfoundationalconcepts
of prolonged relevance, andknowledge ofdetailed attributes ofhardwareand software system com-
ponentsmorelikelyto evolveover time.
The textbook is chartered as support for a single-semester course for beginners to prepare them-
selves for a diversity of roles in supercomputing to pursue their chosen professional career goals. It
is appropriate for future computational scientists who are dedicated to the use of supercomputers to
solve science, engineering, or societal-domain applications, among others. It provides a base-level
descriptionofpossibletargetcapabilitiesforsystemdesignersandengineersinhardwareandsoftware.
It also is a foundation for those who wish to proceed as researchers in supercomputing itself, as an
introductorypresentationofconventionalsystemsandpracticesaswellasarepresentationofthechal-
lengesfacingthisexcitingdomainofexploration.Thebookisequallyappropriateforthoseengagedin
supportingsupercomputingenvironments,suchasdatacenters andsystemadministrators,operators,
and management. In informing future professionals, the textbook can be used in multiple ways. It
servesasareferenceworkofbasicinformationforsupercomputing.Itprovidesasequenceoflecture
contentforclassroomdelivery.Itsupportsahands-onapproachwithsubstantialexamples,allofwhich
canbeexecutedonparallelcomputers,andexercisestoguidestudentsastheylearnbydoing.Itmakes
clearwhereskill-setsandtrainingarepresented,withaneasy-to-learntutorialstyle.Conceptsarepre-
sentedinadetailedbutaccessibleformtoestablishthe“why”ofmethodsconveyedandassistfuture
users in decision-making based on fundamental truths, factors, and sensitivities. Finally, this book
unifieswithinthesamecontextthemanysetsoffactsassociatedwiththemultiplicityofsubdisciplines
that incombination make up the field of supercomputing.
xxi
xxii PREFACE
ORGANIZATION OF THIS BOOK
This textbook serves as a bridge between the reader’s initial curiosity, interests, and requirements in
HPC andthe ultimate knowledge,capabilities,and proficiencytobe acquired through its study. It is
a starting point for those in pursuit of a number of different possible professional paths that share a
commonfoundationinthenatureanduseofthesestate-of-the-artsystems.Whetherthereaderintends
ultimatelytobeabletobuildhardwareorsoftwaresystems,usesuchsystemsasacriticaltoolinthe
pursuitofotherfieldsinscience,engineering,commerce,orsecurity,conductresearchtodevisefuture
means of pushing the state of the art inHPC, oradminister, manage, andmaintain HPC systems for
otherusers,thetextbookisstructuredtocreateaseamlessflowoftopics,eachbenefitingfromthose
precedingwhilecontributingtothefoundationssupportingthosefollowing.Thusthebookpresentsits
major subjects in an order that provides early basic skills of HPC use evenas it conveys underlying
conceptsuponwhichadeeperunderstandingofthesecomplexsystemsandtheiruseisbased.Where
necessary, an introductory view of a topic is givenwith enough informationto consider other topics
that are dependent, only to return in greater depth in later chapters. The readers’ understanding and
capabilities are ratcheted up through incremental enhancement across the diversity of interrelated
topical areas.
Thetextbookisaboutcomputingperformance.Forcurrentandnext-generationsystems,thismeans
theuseandexploitationofworkloadparallelismtoachievescalabilityandthemeansofmanagingdata
toachieveefficiencyofoperation.Thefourprincipaloverarchingsubjectdomainsarelistedbelow.
• System hardware architecture, and enabling technologies.
• Programming models,interfaces, andmethods.
• System software environments, support, andtools.
• Parallel algorithms and distributeddata structures.
Thiswouldsuggestanobviouspedagogical organizationofthetextbookbasedonalogical flow.
But there is another dimension to HPC: alternative strategies for organizing and coordinating paral-
lelism and data management, and the roles of each of the component layers that contribute to them.
This book presentsfour major strategies.
• Jobstream parallelism, throughput, orcapacitycomputing.
• Communicating sequential processes, ormessage passing.
• Multiple-threaded shared memory.
• SIMD orgraphics processing unit(GPU) accelerated.
Fromapedagogicalperspective,theauthorswishtoconveythreekindsofinformationtofacilitate
thelearningprocessandhopefullyalsotheenjoymentofthereader.Atthefoundationallevelarethe
conceptsthatestablishunderstandingoftheunderlyingprinciplesthatguidetheformandfunctionof
HPC.Thereisalotofbasicinformationaswellassomecultural(who,what,when)factsmakingup
thenecessarycollectionofknowledgethatprovidestheframework(scaffolding)ofthefield.Finally,
therearetheskill-setsthatteachhowtodothings.Whileadmittedlynotorthogonaltoeachother,the
textbookapproachesthepresentationofallthematerialineachcaseasoneofthesethreeforms.For
example,chapterswithheadingsthatbegin“TheEssential.”(suchas“TheEssentialOpenMP”)are
crafted as skills modules with a tutorial presentation style for easiest learning. While the mixing of
conceptsandknowledgeisunavoidable,separatesectionsemphasizeoneortheother.Theimportance
PREFACE xxiii
ofthisdistinctionisthatwhilemuchoftheknowledgeaboutthisrapidlyevolvingfield willchange,
andevenbecomeobsoleteinsomecases,thebasic conceptsoffered areinvariantwithtimeandwill
servethereaderwithstronglong-termunderstandingevenasthedetailsofsomespecificmachineor
language may becomelargelyirrelevant over time.
Thistextbookisorganizedfirstaccordingtothefourseparatemodelsofparallelcomputation,and
thenforeachmodelaccordingtotheunderlyingconcepts,therelevantknowledgewithanemphasison
systemarchitecturesthatsupportthem,andtheskillsrequiredtotrainthereaderinhoweachclassof
systemisprogrammed.Inpreparationforthisapproach,someinitialmaterial,includingtheintroduc-
torychapter,providesthebasicpremisesandcontextuponwhichthetextbookisestablished.Eachof
thefourparallelcomputingmodelsisdescribedintermsofconcepts,knowledgedetails,andprogram-
mingskills.Butwhilethiscoversalargepartoftheusefulinformationneededtounderstandandpro-
gramHPCsystems,itmissessomeofthecross-cuttingtopicsrelatedtoenvironmentsandtoolsthatare
animportant,evenpervasive,aspectofthefullcontextofasystemthatmakesittrulyusefulbeyond
thelimitsofanidealizedbeginner’sviewpoint.Afterall,theintentofthetextbookistogivethereader
an effective working ability to take advantage of supercomputers in the professional workplace for
diverse purposes. Thus a number of important and useful tools and methods of their use are given
in aneffectiveorder.Finally, the reader is givenaclear picture ofthewide fieldofHPC, and where
within this broader context the subject matter of this book fits. This can be used to guide planning
forfuturepursuitsandmoreadvancedcoursesselectedinpartbasedonreaders’ultimateprofessional
goals.Theoverall structure andflowofthistextbookare summarized below.
I. INTRODUCTORY AND BASIC IDEAS (CHAPTERS 1 AND 4)
These chapters provide a firm grounding on the basics, including an introduction to the domains of
executionmodels,architectureconcepts,performanceandparallelismmetrics,andthedominantclass
ofparallelcomputingsystems(commodityclusters).Theygiveafirstexperiencewithrunningparallel
programsthroughtheuse ofaspecial kind ofbenchmarksthatallowmeasurement andcomparisons
amongdifferent HPC systems.It is here thata sense ofthe history, the evolutionofthe contributing
ideas,and the cultureof the field is first giventothe reader.
II. THROUGHPUT COMPUTING FOR JOB-STREAM PARALLELISM
(CHAPTERS 5 AND 11)
Although among the simplest ways to take advantage of parallel computers, throughput computing
(also referred to as capacity computing) as widely used is sufficient for many objectives and
workflows. It can also prove to be among the most efficient, as it usually exhibits the most coarse-
grained tasks and a minimum of control overheads. Widely used middleware that manages
job-stream workloads such as SLURM and PBS are given in tutorial form for both independent
jobs and relatedsets, such as parameter sweeps and Monte Carlosimulations.
III. SHARED-MEMORY MULTITHREADED COMPUTING (CHAPTERS 6 AND 7)
Oneofthedominantmodelsofuserparallelprocessingistask(orthread)parallelisminthecontextof
sharedmemory.Alltheuserdatacan bedirectlyaccessedbyanyoftheuserthreads,andsequential
xxiv PREFACE
consistency is assumed by hardware cache coherence. This part of the book describes this parallel
executionmodel,thecharacteristicsofshared-memorymultiprocessors,andtheOpenMPparallelpro-
gramming language.
IV. MESSAGE-PASSING COMPUTING (CHAPTER 8)
Fortrulyscalableparallelcomputingthatmayemployamillioncoresormoreonasingleapplication,
thedistributed-memoryarchitectureandcommunicatingsequentialprocessingexecutionmodelisthe
dominantapproach.ThispartofthebookbuildsontopicsassociatedwiththenodesusedforSMPsand
theclusterapproachpreviouslydescribedforthroughputcomputingbyaddingthesemanticsofmes-
sage passing, collective operations, and global synchronization. It is in this section that message-
passinginterface(MPI)istaught,thesinglemostwidelyemployedprogramminginterfaceforscalable
science and engineeringapplications.
V. ACCELERATING GPU COMPUTING (CHAPTERS 15 AND 16)
For certain widely used dataflow patterns, higher-level structures of specialized cores can provide
exceptionalperformanceandenergyefficiency.Suchsubsystems,classifiedinthemostgeneralsense
as“accelerators,”canspeedupapplicationsbymanytimes,sometimesbyoveranorderofmagnitude.
AlsoreferredtoasGPGPUs,theseoftentaketheformofattachedarrayprocessors,butinsomecases
arebeingintegratedwithinsingle-socketpackagesoreventhesamedie.Thispartofthetextbookde-
scribesGPUstructures,availableproducts,andprogramming,withanemphasisononeprogramming
interface, OpenACC.
VI. BUILDING SIGNIFICANT PROGRAMS (CHAPTERS 9, 10, AND 12e14)
BythispointinthebookthereaderiswellacquaintedwiththeprimarymodesofHPC,knowstherules
for the principal programming interfaces, and has hands-on experience with making basic parallel
functionsworkwithintheseframeworks.Butformorecomplicated,moresophisticated,moreuseful,
andfranklymoreprofessionalsupercomputingprogramsanumberofadditionalmethodsandtoolsare
required.ThissegmentofthetextbooktakestheHPCnovicefromthebeginnerleveltothatofuseful
apprentice.Severalkeytopicsandskillsareintroducedheretogivethestudentthenecessaryabilities
tobeusefulinsystemdesignandapplication.Firstamongtheseisabroadarrayofparallelalgorithms
foradiversesetofneeds.Manyofthesearealreadymadeavailableincollectionsknownas“libraries”
that can savethe application developer an enormous amount of time, if appropriately used. To get a
program from its first draft to its final correct and efficient form requires a combined approach
involvingparalleldebuggingforcorrectnessofanswersandperformanceoptimizationthroughoper-
ation monitoring. Tools and methods for both are presented here, including the detailed skill-sets
required.Finally,HPCrunstendtoproduceenormousamountsofdatadasmuchasterabytesorpeta-
bytesofresultsinasingleexecution.Scientificvisualization,theproducingofimagesorevenmovies
fromsuchmassivedatasets,istheonlypracticalwaytoachieveunderstandingoftheresultsofatech-
nicalcomputingsimulation.Examplesofwidelyusedtoolsforthispurposearepresented,withessen-
tial techniques tomakethem useful.