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  • What is JIT compiler and interpreter in Java?

    The JIT compiler helps improve the performance of Java programs by compiling bytecodes into native machine code at run time. The JIT compiler is enabled by default. When a method has been compiled, the JVM calls the compiled code of that method directly instead of interpreting it.

  • Is JIT a compiler or interpreter?

    For example, in the Java programming language and environment, a just-in-time (JIT) compiler turns Java bytecode -- a program that contains instructions that must be interpreted -- into instructions that can be sent directly to the processor.

  • What is the difference between JIT and interpreter in Java?

    Interpreter: Reads your source code or some intermediate representation (bytecode) of it, and executes it directly. JIT compiler: Reads your source code, or more typically some intermediate representation (bytecode) of it, compiles that on the fly and executes native code.
  • JIT compiles bytecode to native machine code to optimise efficiency. JVM interprets the same sequence of bytecode repeatedly and incurs a longer execution time. The hardware executes the native code of repeated method calls. JIT compiler is a part of the JVM.

Fernando Magno Quintão Pereira

fernando@dcc.ufmg.br

PROGRAM ANALYSIS AND OPTIMIZATION - DCC888

JUST-IN-TIME COMPILATION

AToyExample

#include #include #include int main(void) { char* program; int (*fnptr)(void); int a; program = mmap(NULL, 1000, PROT_EXEC | PROT_READ | PROT_WRITE, MAP_PRIVATE | MAP_ANONYMOUS, 0, 0); program[0] = 0xB8; program[1] = 0x34; program[2] = 0x12; program[3] = 0; program[4] = 0; program[5] = 0xC3; fnptr = (int (*)(void)) program; a = fnptr(); printf("Result = %X\n",a);}1) Whatistheprogramontheleftdoing?2) WhatisthisAPIallabout?3) Whatdoesthisprogramhavetodowithajust-in-timecompiler?

AToyExample

#include #include #include int main(void) { char* program; int (*fnptr)(void); int a; program = mmap(NULL, 1000, PROT_EXEC | PROT_READ | PROT_WRITE, MAP_PRIVATE | MAP_ANONYMOUS, 0, 0); program[0] = 0xB8; program[1] = 0x34; program[2] = 0x12; program[3] = 0; program[4] = 0; program[5] = 0xC3; fnptr = (int (*)(void)) program; a = fnptr(); printf("Result = %X\n",a);}

AToyExample

#include #include #include int main(void) { char* program; int (*fnptr)(void); int a; program = mmap(NULL, 1000, PROT_EXEC | PROT_READ | PROT_WRITE, MAP_PRIVATE | MAP_ANONYMOUS, 0, 0); program[0] = 0xB8; program[1] = 0x34; program[2] = 0x12; program[3] = 0; program[4] = 0; program[5] = 0xC3; fnptr = (int (*)(void)) program; a = fnptr(); printf("Result = %X\n",a);}

AToyExample

#include #include #include int main(void) { char* program; int (*fnptr)(void); int a; program = mmap(NULL, 1000, PROT_EXEC | PROT_READ | PROT_WRITE, MAP_PRIVATE | MAP_ANONYMOUS, 0, 0); program[0] = 0xB8; program[1] = 0x34; program[2] = 0x12; program[3] = 0; program[4] = 0; program[5] = 0xC3; fnptr = (int (*)(void)) program; a = fnptr(); printf("Result = %X\n",a);}

Just-in-TimeCompilers

• AJITcompilertranslatesaprogramintobinarycodewhilethisprogramisbeingexecuted. • Wecancompileafunctionassoonasitisnecessary. - ThisisGoogle'sV8approach. • Orwecanfirstinterpretthefunction,andafterwe - ThisistheapproachofMozilla'sIonMonkey.

TherearemanyJITcompilersaround

• JavaHotspotisoneofthemostefficientJITcompilersinusetoday.Itwasreleasedin1999,andhasbeeninusesincethen.

• V8istheJavaScriptJITcompilerusedbyGoogleChrome.• IonMonkeyistheJavaScriptJITcompilerusedbythe

MozillaFirefox.

• LuaJIT(http://luajit.org/)isatracebasedjust-in- • The.NetframeworkJITsCILcode.• ForPythonwehavePyPy,whichrunsonCpython.

CanJITscompetewithstaticcompilers?

Tradeoffs

• TherearemanytradeoffsinvolvedintheJITcompilationofaprogram. • Thetimetocompileispartofthetotalexecutiontimeof theprogram. • Wemaybewillingtorunsimplerandfaster • Andwemaytrytolookatruntimeinformationto producebettercodes. - Profilingisabigplayerhere. • Thesamecodemaybecompiledmany times!

Whywouldwecompilethesamecodemanytimes?

Example:Mozilla'sIonMonkey

ParserOptimizer

Code

Generator

function inc(x) { return x + 1;

JavaScript source code

mov 0x28(%rsp),%r10 shr $0x2f,%r10 cmp $0x1fff1,%r10d je 0x1b jmpq 0x6e mov 0x28(%rsp),%rax mov %eax,%ecx mov $0x7f70b72c,%r11 mov (%r11),%rdx cmp %rdx,%rsp jbe 0x78 add $0x1,%ecx jo 0xab mov $0xfff88000,%rax retq

Native codeBytecodes

00000: getarg 0

00003: one

00004: add

00005: return

00006: stop

LIR label () parameter ([x:1 (arg:0)]) parameter ([x:2 (arg:8)]) start () unbox ([i:3]) (v2:r) checkoverrecursed()t=([i:4]) osipoint () addi ([i:5 (!)]) (v3:r), (c) box ([x:6]) (v5:r) return () (v6:rcx) resumepoint 4 2 6 parameter -1 Value resumepoint 4 2 6 parameter 0 Value constant undef Undefined start unbox parameter4 Int32 resumepoint 4 2 6 checkoverrecursed constant 0x1 Int32 add unbox10 const14 Int32 return add16

MIRInterpreterCompiler

WhentoInvoketheJITCompiler?

• Compilationhasacost. - Functionsthatexecuteonlyonce,forafewiterations, shouldbeinterpreted. • Compiledcoderunsfaster. - Functionsthatarecalledoften,orthatloopforalongtime shouldbecompiled. • Andwemayhavedifferentoptimizationlevels...

Howtodecidewhentocompileapieceofcode?

TheCompilationThreshold

Interpreted CodeUnoptimized Native CodeOptimized Native CodeBaseline CompilerOptimizing CompilerNumber of instructions processed (either natively or via interpretation)Number of instructions compiledTime

TheMillion-DollarsQuestion

• WhentoinvoketheJITcompiler?

1) CanyoucomeupwithastrategytoinvoketheJITcompilerthatoptimizesforspeed?2) DoyouhavetoexecutetheprogramabitbeforecallingtheJIT?3) Howmuchinformationdoyouneedtomakeagoodguess?4) Whatisthepriceyoupayformakingawrongprediction?5) Whichprogramsareeasytopredict?6) Dotheeasyprogramsreflecttheneedsoftheusers?

SPECULATION

fernando@dcc.ufmg.br

Speculation

• AkeytrickusedbyJITcompilersisspeculation. • Wemayassumethatagivenpropertyistrue,andthen • Therearemanydifferentkindsofspeculation,andthey arealwaysagamble:

Speculation

• AkeytrickusedbyJITcompilersisspeculation. • Wemayassumethatagivenpropertyistrue,andthen • Therearemanydifferentkindsofspeculation,andthey arealwaysagamble: - Let'sassumethatthetypeofavariableisaninteger, • butifwehaveanintegeroverflow... - Let'sassumethatthepropertiesoftheobjectare fixed, • butifweaddorremovesomethingfromtheobject... - Let'sassumethatthetargetofacallisalwaysthe same, • butifwepointthefunctionreferencetoanother closure...

InlineCaching

• Oneoftheearliest,andmosteffective,typesofspecializationwasinlinecaching,anoptimizationdevelopedfortheSmalltalkprogramminglanguage

F

• Smalltalkisadynamicallytypedprogramminglanguage.• Inanutshell,objectsarerepresentedashash-tables.• Thisisaveryflexibleprogrammingmodel:wecanaddor

removepropertiesofobjectsatwill. • LanguagessuchasPythonandRubyalsoimplement objectsinthisway. • Today,inlinecachingisthekeyideabehindJITs'shigh F

VirtualTables

1) Inorderforthistricktowork,weneedtoimposesomerestrictionsonvirtualtables.Whichones?2) Whatarethevirtualtablesof?Animala=newAnimal();Animalm=newMammal();Mammald=newDog()

VirtualTables

Animal

toString eat

Mammal

toString eat suckMilk Dog toString eat suckMilk bark

Animal aAnimal mMammal d

Howtolocatethetargetofd.eat()?

VirtualCall

Dog toString eat suckMilk bark

Mammal dd.eat()

First, we need to know the table d is pointing to. This requires one pointer dereference:

Second, we need to know the offset

of the method eat, inside the table.

This offset is always the same for

any class that inherits from Animal, so we can jump blindly.

Animal

toString eat

Mammal

toString eat suckMilk public void eat() {

System.out.println ("Eats like a dog");

public void eat() {

System.out.println ("Eats like a mammal");

public void eat() {

System.out.println ("Eats like an animal");

ObjectsinPython

INT_BITS = 32def getIndex(element): index = element / INT_BITS offset = element % INT_BITS bit = 1 << offset return (index, bit)class Set: def __init__(self, capacity): self.capacity = capacity self.vector = range(1+capacity/INT_BITS) for i in range(len(self.vector)): self.vector[i] = 0 def add(self, element): (index, bit) = getIndex(element) self.vector[index] |= bitclass ErrorSet(Set): def checkIndex(self, element): if (element > self.capacity): raise IndexError(str(element) + " is out of range.") def add(self, element): self.checkIndex(element) Set.add(self, element) print element, "successfully added."

1) Whatistheprogramontheleftdoing?2) WhatisthecomplexitytolocatethetargetofamethodcallinPython?3) Whycan'tcallsinPythonbeimplementedasefficientlyascallsinJava?

UsingPythonObjects

def fill(set, b, e, s): for i in range(b, e, s): set.add(i)s0 = Set(15)fill(s0, 10, 20, 3)s1 = ErrorSet(15)fill(s1, 10, 14, 3)class X: def __init__(self): self.a = 0fill(X(), 1, 10, 3)>>> AttributeError: X instance>>> has no attribute 'add'1) Whatdoesthefunctionfilldo?2) Whydidthethirdcalloffillfailed?3) Whataretherequirementsthatfillexpectsonitsparameters?

DuckTyping

def fill(set, b, e, s): for i in range(b, e, s): set.add(i)class Num: def __init__(self, num): self.n = num def add(self, num): self.n += num def __str__(self): return str(self.n)n = Num(3)print nfill(n, 1, 10, 1)...Dowegetanerrorhere?

DuckTyping

class Num: def __init__(self, num): self.n = num def add(self, num): self.n += num def __str__(self): return str(self.n)n = Num(3)print nfill(n, 1, 10, 1)print n>>> 3>>> 48

ThePriceofFlexibility

• Objects,inthesedynamicallytypedlanguages,areforthemostpartimplementedashashtables. - Thatiscool:wecanaddorremovemethodswithoutmuch hardwork. def fill(set, b, e, s): for i in range(b, e, s): set.add(i) - Andmindhowmuchcodewecanreuse? • Butmethodcallsarepretty expensive.

Mammal d

__init__(self, cap)add(self, elem)del(self, elem)contains(self, elem)

Howcanwemakethesecallscheaper?

MonomorphicInlineCache

class Num: def __init__(self, n): self.n = n def add(self, num): self.n += numdef fill(set, b, e, s): for i in range(b, e, s): set.add(i)n = Num(3)print nfill(n, 1, 10, 1)print n>>> 3>>> 48

InliningontheMethod

• Wecanalsospeculateonthemethodname,insteadofdoingitonthecallingsite:

1) Isthereanyadvantagetothisapproach,whencomparedtoinliningatthecallsite?2) Isthereanydisadvantage?3) Whichoneislikelytochangemoreoften?

PolymorphicCalls

• Ifthetargetofacallchangesduringtheexecutionoftheprogram,thenwehaveapolymorphiccall. • Amonomorphicinlinecachewouldhavetobe >>> l = [Num(1), Set(1), Num(2), Set(2), Num(3), Set(3)]>>> for o in l:... o.add(2)...

PolymorphicCalls

• Ifthetargetofacallchangesduringtheexecutionoftheprogram,thenwehaveapolymorphiccall. • Amonomorphicinlinecachewouldhavetobe >>> l = [Num(1), Set(1), Num(2), Set(2), Num(3), Set(3)]>>> for o in l:... o.add(2)...

TheSpeculativeNatureofInlineCaching

• Python-aswellasJavaScript,Ruby,Luaandotherverydynamiclanguages-allowstheusertoaddorremovemethodsfromanobject.

• Ifsuchchangesinthe

TheBenefitsoftheInlineCache

• Monomorphicinlinecachehit: - 10instructions • PolymorphicInlinecachehit: - 35instructionsifthereare10types- 60instructionsifthereare20types • Inlinecachemiss:1,000-4,000instructions. F F

Whichfactorscouldjustifythesenumbers?

VALUESPECIALIZATION

fernando@dcc.ufmg.br

Functionsareoftencalledwithsamearguments

• Costaetal.haveinstrumentedtheMozillaFirefoxbrowser,andhaveusedittonavigatethroughthe100mostvisitedwebpagesaccordingtotheAlexaindex

F • Theyhavealsoperformedthesetestsonthreepopular benchmarksuites: - Sunspider1.0,V86.0andKraken1.1 F : http://www.alexa.com F

ManyFunctionsareCalledonlyOnce!

MostFunctionsareCalledwithSameArguments

ASimilarPatternintheBenchmarks

Sunspider 1.0V8 version 6Kraken 1.1Sunspider 1.0V8 version 6Kraken 1.1

So,ifitislikethis...

• Let'sassumethatthefunctionisalwayscalledwiththesamearguments.Wegeneratethebestcodespecifictothosearguments.Ifthefunctioniscalledwithdifferentarguments,thenwere-compileit,thistimeusingamoregenericapproach.

function sum(N) { if(typeof N != 'number') return 0; var s = 0; for(var i=0; i

ARunningExample-LinearSimilaritySearch

function closest(v, q, n) { if (n == 0) { throw "Error"; } else { var i = 0; var d = 2147483647; while (i < n) { var nd = abs(s[i] - q); if (nd <= d) d = nd; i++; } return d; }}

Givenavectorvofsizen,holdingintegers,findtheshortestdifferencedfromanyelementinvtoaparameterq.Wemustiteratethroughv,lookingforthesmallestdifferencev[i] - q.ThisisanO(n)algorithm.

Function entry point

v = param[0] q = param[1] n = param[2] if (n == 0) goto L 1 L1: throw "Error" L2: i 0 = 0 d 0 = 2147483647 L3: i 1 =ϕ (i 0 , i 2 , i 3 d 1 =ϕ (d 0 , d 3 , d 4 if (i 1 < n) goto L5 L4: return d 1 L5: t 0 = 4 * i t 1 = v[t 0 inbounds(t 1 , n) goto L8 L6: d 2 = nd L9: d 3 =ϕ (d 1 , d 2 i 2 = i 1 + 1 goto L3

On stack replacement

v = param[0] q = param[1] n = param[2] i 3 = stack[0] d 4 = stack[1]

L7: nd = abs(t

1 , q) if (nd > d 1 ) goto L9 L8: throw BoundsErr

TheControlFlowGraphoftheExample

function closest(v, q, n) { if (n == 0) { throw "Error"; } else { var i = 0; var d = 2147483647; while (i < n) { var nd = abs(s[i]-q); if (nd <= d) d = nd; i++; } return d; }}

Function entry point

v = param[0] q = param[1] n = param[2] if (n == 0) goto L 1 L1: throw "Error" L2: i 0 = 0 d 0 = 2147483647 L3: i 1 =ϕ (i 0 , i 2 , i 3 d 1 =ϕ (d 0 , d 3 , d 4 if (i 1 < n) goto L5 L4: return d 1 L5: t 0 = 4 * i t 1 = v[t 0 inbounds(t 1 , n) goto L8 L6: d 2 = nd L9: d 3 =ϕ (d 1 , d 2 i 2 = i 1 + 1 goto L3

On stack replacement

v = param[0] q = param[1] n = param[2] i 3 = stack[0] d 4 = stack[1]

L7: nd = abs(t

1 , q) if (nd > d 1 ) goto L9 L8: throw BoundsErr

TheControlFlowGraphoftheExample

function closest(v, q, n) { if (n == 0) { throw "Error"; } else { var i = 0; var d = 2147483647; while (i < n) { var nd = abs(s[i]-q); if (nd <= d) d = nd; i++; } return d; }}

vqnload[0]42100idheapstack

2147483647

40

Function entry point

v = load[0] q = 42 n = 100quotesdbs_dbs17.pdfusesText_23
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