Know Your Engines How to
Make Your JavaScript Fast Dave Mandelin June 15, 2011 O’Reilly Velocity

5 years of progress... 10
JavaScript 7.5 C run time vs. C 5 2.5 0 2006 2008 2011 one program on one popular browser: 10x faster!

...lost in an instant! function
f() { var sum = 0; for (var i = 0; i < N; ++i) { sum += i; } } function f() { eval(“”); var sum = 0; for (var i = 0; i < N; ++i) { sum += i; } }

...lost in an instant! function
f() { 80 var sum = 0; for (var i = 0; i < N; ++i) { sum += i; 60 } } 40 20 function f() { eval(“”); 0 without eval with eval var sum = 0; for (var i = 0; i < N; ++i) { sum += i; with eval(“”) up to } } 10x slower!

Making JavaScript Fast Or, Not
Making JavaScript Slow How JITs make JavaScript not slow How not to ruin animation with pauses How to write JavaScript that’s not slow

The 2006 JavaScript Engine

Inside the 2006 JS Engine
DOM Standard Front End Interpreter Library Garbage Collector

Inside the 2006 JS Engine
// JavaScript source e.innerHTML = n + “ items”; DOM Standard Front End Interpreter Library Garbage Collector

Inside the 2006 JS Engine
// JavaScript source e.innerHTML = n + “ items”; DOM Standard Front End Interpreter Library // bytecode (AST in some engines) Garbage tmp_0 = add var_1 str_3 Collector setprop var_0 ‘innerHTML’ tmp_0

Inside the 2006 JS Engine
// JavaScript source e.innerHTML = n + “ items”; DOM Standard Front End Interpreter Library Run the bytecode // bytecode (AST in some engines) Garbage tmp_0 = add var_1 str_3 Collector setprop var_0 ‘innerHTML’ tmp_0

Inside the 2006 JS Engine
// JavaScript source e.innerHTML = n + “ items”; DOM Standard Front End Interpreter Library Run the bytecode Reclaim memory // bytecode (AST in some engines) Garbage tmp_0 = add var_1 str_3 Collector setprop var_0 ‘innerHTML’ tmp_0

Inside the 2006 JS Engine
Set innerHTML // JavaScript source e.innerHTML = n + “ items”; DOM Standard Front End Interpreter Library Run the bytecode Reclaim memory // bytecode (AST in some engines) Garbage tmp_0 = add var_1 str_3 Collector setprop var_0 ‘innerHTML’ tmp_0

Why it’s hard to make
JS fast Because JavaScript is an untyped language. untyped = no type declarations

Operations in an untyped language
x = y + z can mean many things • if y and z are numbers, numeric addition • if y and z are strings, concatenation • and many other cases; y and z can have different types

Engine-Internal Types JS engines use
finer-grained types internally. JavaScript type number object

Engine-Internal Types JS engines use
finer-grained types internally. JavaScript type Engine type number 32-bit* integer 64-bit floating-point object

Engine-Internal Types JS engines use
finer-grained types internally. JavaScript type Engine type number 32-bit* integer 64-bit floating-point { a: 1 } { a: 1, b: 2 } object { a: get ... } { a: 1, __proto__ = new C }

Engine-Internal Types JS engines use
finer-grained types internally. JavaScript type Engine type number 32-bit* integer 64-bit floating-point { a: 1 } { a: 1, b: 2 } Different object { a: get ... } shapes { a: 1, __proto__ = new C }

Values in an untyped language
Because JavaScript is untyped, the interpreter needs boxed values. Boxed Unboxed Purpose Storage Computation Examples (INT, 55) 55 (STRING, “foo”) “foo” Definition (type tag, C++ value) C++ value only boxed values can be stored in variables, only unboxed values can be computed with (+, *, etc)

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z:

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory ‣ check the types of y and z and choose the action

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x ‣ write the boxed output x to memory

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z This is the only real work! ‣ execute the action ‣ box the output x ‣ write the boxed output x to memory

Running Code in the Interpreter
Here’s what the interpreter must do to execute x = y + z: ‣ read the operation x = y + z from memory ‣ read the boxed inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z This is the only real work! ‣ execute the action ‣ box the output x Everything else is ‣ write the boxed output x to memory overhead.

The 2011 JavaScript Engine

Inside the 2011 JS Engine
Garbage Collector DOM Interpreter JavaScript source Standard Library Front End bytecode/AST

Inside the 2011 JS Engine
Garbage Collector DOM Interpreter JavaScript source Standard Library Front End JIT Compiler Compile to x86/x64/ARM bytecode/AST

Inside the 2011 JS Engine
Garbage Collector DOM Interpreter JavaScript source Standard Library Fast! x86/x64/ARM Front End JIT Compiler Compile to x86/x64/ARM CPU bytecode/AST

Inside the 2011 JS Engine
Garbage Collector DOM Interpreter JavaScript source Standard Library Fast! x86/x64/ARM Front End JIT Compiler Compile to x86/x64/ARM CPU Type-Specializing bytecode/AST JIT Compiler Ultra Fast!

Inside the 2011 JS Engine
Garbage Collector DOM Interpreter JavaScript source Standard Library Fast! x86/x64/ARM Front End JIT Compiler Compile to x86/x64/ARM CPU Type-Specializing bytecode/AST JIT Compiler Ultra Fast!

Inside the 2011 JS Engine
THE Garbage DOM Collector SLOW ZONE Interpreter JavaScript source Standard Library Fast! x86/x64/ARM Front End JIT Compiler Compile to x86/x64/ARM CPU Type-Specializing bytecode/AST JIT Compiler Ultra Fast!

Running Code with the JIT
All Major The basic JIT compiler on x = y + z: Browsers ‣ read the operation x = y + z from memory ‣ read the inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x ‣ write the output x to memory

Running Code with the JIT
All Major The basic JIT compiler on x = y + z: Browsers ‣ read the operation x = y + z from memory CPU does it for us! ‣ read the inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x ‣ write the output x to memory

Running Code with the JIT
All Major The basic JIT compiler on x = y + z: Browsers ‣ read the operation x = y + z from memory CPU does it for us! ‣ read the inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x ‣ write the output x to memory JIT code can keep things in registers

Choosing the action in the
JIT

Choosing the action in the
JIT • Many cases for operators like +

Choosing the action in the
JIT • Many cases for operators like + • Engines generate fast JIT code for “common cases” • number + number • string + string

Choosing the action in the
JIT • Many cases for operators like + • Engines generate fast JIT code for “common cases” • number + number • string + string • “Rare cases” run in the slow zone • number + undefined

JITs for Regular Expressions All
Major Browsers • There is a separate JIT for regular expressions • Regular expressions are generally faster than manual search • Still in the slow zone: • Some complex regexes (example: backreferences) • Building result arrays (test much faster than exec)

Object Properties function f(obj) {
return obj.a + 1; }

Object Properties function f(obj) {
return obj.a + 1; } • Need to search obj for a property named a slow

Object Properties function f(obj) {
return obj.a + 1; } • Need to search obj for a property named a slow • May need to search prototype chain up several levels super-slow

Object Properties function f(obj) {
return obj.a + 1; } • Need to search obj for a property named a slow • May need to search prototype chain up several levels super-slow • Finally, once we’ve found it, get the property value fast!

ICs: a mini-JIT for objects
All Major Browsers

ICs: a mini-JIT for objects
All Major Browsers • Properties become fast with inline caching (we prefer IC)

ICs: a mini-JIT for objects
All Major Browsers • Properties become fast with inline caching (we prefer IC) • Basic plan:

ICs: a mini-JIT for objects
All Major Browsers • Properties become fast with inline caching (we prefer IC) • Basic plan: 1. First time around, search for the property in the Slow Zone

ICs: a mini-JIT for objects
All Major Browsers • Properties become fast with inline caching (we prefer IC) • Basic plan: 1. First time around, search for the property in the Slow Zone 2. But record the steps done to actually get the property

ICs: a mini-JIT for objects
All Major Browsers • Properties become fast with inline caching (we prefer IC) • Basic plan: 1. First time around, search for the property in the Slow Zone 2. But record the steps done to actually get the property 3. Then JIT a little piece of code that does just that

ICs: Example Example Code var
obj1 = { a: 1, b: 2, c: 3 }; var obj2 = { b: 2 }; function f(obj) { return obj.b + 1; }

ICs: Example Example Code var
obj1 = { a: 1, b: 2, c: 3 }; var obj2 = { b: 2 }; function f(obj) { return obj.b + 1; } Generated JIT Code ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code shape=12,
in position 1 var obj1 = { a: 1, b: 2, c: 3 }; var obj2 = { b: 2 }; function f(obj) { return obj.b + 1; } Generated JIT Code ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code icStub_1:
shape=12, in position 1 compare obj.shape, 12 var obj1 = { a: 1, b: 2, c: 3 }; jumpIfFalse slowPropAccess var obj2 = { b: 2 }; load obj.props[1] jump continue_1 function f(obj) { return obj.b + 1; } Generated JIT Code ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code icStub_1:
shape=12, in position 1 compare obj.shape, 12 var obj1 = { a: 1, b: 2, c: 3 }; jumpIfFalse slowPropAccess var obj2 = { b: 2 }; load obj.props[1] jump continue_1 function f(obj) { return obj.b + 1; } Generated JIT Code ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code icStub_1:
shape=12, in position 1 compare obj.shape, 12 var obj1 = { a: 1, b: 2, c: 3 }; jumpIfFalse slowPropAccess var obj2 = { b: 2 }; load obj.props[1] jump continue_1 function f(obj) { return obj.b + 1; } Generated JIT Code ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code icStub_1:
shape=12, in position 1 compare obj.shape, 12 var obj1 = { a: 1, b: 2, c: 3 }; jumpIfFalse slowPropAccess var obj2 = { b: 2 }; load obj.props[1] shape=15, in position 0 jump continue_1 function f(obj) { return obj.b + 1; } Generated JIT Code ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code icStub_1:
shape=12, in position 1 compare obj.shape, 12 var obj1 = { a: 1, b: 2, c: 3 }; jumpIfFalse slowPropAccess var obj2 = { b: 2 }; load obj.props[1] shape=15, in position 0 jump continue_1 function f(obj) { return obj.b + 1; } icStub_2: compare obj.shape, 15 jumpIfFalse slowPropAccess Generated JIT Code load obj.props[0] jump continue_1 ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code icStub_1:
shape=12, in position 1 compare obj.shape, 12 var obj1 = { a: 1, b: 2, c: 3 }; jumpIfFalse slowPropAccess var obj2 = { b: 2 }; load obj.props[1] shape=15, in position 0 jump continue_1 function f(obj) { return obj.b + 1; } icStub_2: compare obj.shape, 15 jumpIfFalse slowPropAccess Generated JIT Code load obj.props[0] jump continue_1 ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

ICs: Example Example Code icStub_1:
shape=12, in position 1 compare obj.shape, 12 var obj1 = { a: 1, b: 2, c: 3 }; jumpIfFalse slowPropAccess var obj2 = { b: 2 }; load obj.props[1] shape=15, in position 0 jump continue_1 function f(obj) { return obj.b + 1; } icStub_2: compare obj.shape, 15 jumpIfFalse slowPropAccess Generated JIT Code load obj.props[0] jump continue_1 ... jump slowPropAccess slowPropAccess: continue_1: ... set up call ... call ICGetProp ; C++ Slow Zone jump continue_1

These are fast because of
ICs Global Variable Access var q = 4; var r; function f(obj) { r = q; }

These are fast because of
ICs Global Variable Access var q = 4; var r; function f(obj) { r = q; } Direct Property Access var obj1 = { a: 1, b: 2, c: 3 }; var obj2 = { b: 2 }; function f(obj) { obj2.b = obj1.c; }

These are fast because of
ICs Global Variable Access Closure Variable Access var q = 4; var f = function() { var r; var x = 1; var g = function() { function f(obj) { var sum = 0; r = q; for (var i = 0; i < N; ++i) { } sum += x; } return sum; Direct Property Access } return g(); var obj1 = { a: 1, b: 2, c: 3 }; } var obj2 = { b: 2 }; function f(obj) { obj2.b = obj1.c; }

Prototypes don’t hurt much function
A(x) { this.x = x; } function B(y) { this.y = y; } B.prototype = new A; function C(z) { this.z = z; } C.prototype = new B;

Prototypes don’t hurt much new
A function A(x) { this.x = x; } new B function B(y) { proto this.y = y; } new C(1) B.prototype = new A; function C(z) { this.z = z; } C.prototype = new B;

Prototypes don’t hurt much new
A function A(x) { this.x = x; } new B function B(y) { proto this.y = y; } new C(1) new C(2) B.prototype = new A; function C(z) { this.z = z; } C.prototype = new B;

Prototypes don’t hurt much new
A function A(x) { this.x = x; } new B function B(y) { proto this.y = y; } new C(1) new C(2) new C(3) B.prototype = new A; function C(z) { this.z = z; } C.prototype = new B;

Prototypes don’t hurt much new
A function A(x) { this.x = x; } new B function B(y) { proto this.y = y; } new C(1) new C(2) new C(3) B.prototype = new A; function C(z) { this.z = z; Shape of new C objects determines prototype } C.prototype = new B;

Prototypes don’t hurt much new
A function A(x) { this.x = x; } new B function B(y) { proto this.y = y; } new C(1) new C(2) new C(3) B.prototype = new A; function C(z) { this.z = z; Shape of new C objects determines prototype } C.prototype = new B; -> IC can generate code that checks shape, then reads directly from prototype without walking

Many Shapes Slow Down ICs
What happens if many shapes of obj are passed to f? function f(obj) { return obj.p; } ICs end up looking like this:

Many Shapes Slow Down ICs
What happens if many shapes of obj are passed to f? function f(obj) { return obj.p; } ICs end up looking like this: jumpIf shape != 12 read for shape 12

Many Shapes Slow Down ICs
What happens if many shapes of obj are passed to f? function f(obj) { return obj.p; } ICs end up looking like this: jumpIf shape != 12 read for shape 12 jumpIf shape != 15 read for shape 15

Many Shapes Slow Down ICs
What happens if many shapes of obj are passed to f? function f(obj) { return obj.p; } ICs end up looking like this: jumpIf shape != 12 read for shape 12 jumpIf shape != 15 read for shape 15 jumpIf shape != 6 read for shape 6

Many Shapes Slow Down ICs
What happens if many shapes of obj are passed to f? function f(obj) { return obj.p; } ICs end up looking like this: ... jumpIf shape != 12 jumpIf shape != 16 read for shape 12 read for shape 16 jumpIf shape != 15 jumpIf shape != 22 read for shape 15 read for shape 22 jumpIf shape != 6 jumpIf shape != 3 read for shape 6 read for shape 3

Many shapes in practice 100
IE IE Slow Zone for 2+ shapes Opera Chrome 75 Opera # of shapes doesn’t matter! nanoseconds/iteration Firefox Safari 50 Chrome more shapes -> slower Firefox 25 slower with more shapes, but levels off in Slow Zone Safari 0 1 2 8 16 32 100 200 # of shapes at property read site

Deeply Nested Closures are Slower
var f = function() { var x; var g = function() { var h = function() { var y; var i = function () { var j = function() { z = x + y;

Deeply Nested Closures are Slower
var f = function() { f call object var x; var g = function() { var h = function() { h call object var y; var i = function () { var j = function() { j call object z = x + y; First call to f

Deeply Nested Closures are Slower
var f = function() { f call object f call object var x; var g = function() { var h = function() { h call object h call object var y; var i = function () { var j = function() { j call object j call object z = x + y; First call to f Second call to f

Deeply Nested Closures are Slower
var f = function() { f call object f call object var x; var g = function() { var h = function() { h call object h call object var y; var i = function () { var j = function() { j call object j call object z = x + y; First call to f Second call to f • Prototype chains don’t slow us down, but deep closure nesting does. Why?

Deeply Nested Closures are Slower
var f = function() { f call object f call object var x; var g = function() { var h = function() { h call object h call object var y; var i = function () { var j = function() { j call object j call object z = x + y; First call to f Second call to f • Prototype chains don’t slow us down, but deep closure nesting does. Why? • Every call to f generates a unique closure object to hold x.

Deeply Nested Closures are Slower
var f = function() { f call object f call object var x; var g = function() { var h = function() { h call object h call object var y; var i = function () { var j = function() { j call object j call object z = x + y; First call to f Second call to f • Prototype chains don’t slow us down, but deep closure nesting does. Why? • Every call to f generates a unique closure object to hold x. • The engine must walk up to x each time

Properties in the Slow Zone

Properties in the Slow Zone
Undefined Property (Fast on Firefox, Chrome) var a = {}; a.x;

Properties in the Slow Zone
Undefined Property (Fast on Firefox, Chrome) var a = {}; a.x; DOM Access (I only tested .id, so take with a grain of salt-- other properties may differ) var a = document.getByElementId(“foo”); a.id;

Properties in the Slow Zone
Undefined Property Scripted Getter (Fast on Firefox, Chrome) (Fast on IE) var a = {}; var a = { x: get() { return 1; } }; a.x; a.x; DOM Access (I only tested .id, so take with a grain of salt-- other properties may differ) var a = document.getByElementId(“foo”); a.id;

Properties in the Slow Zone
Undefined Property Scripted Getter (Fast on Firefox, Chrome) (Fast on IE) var a = {}; var a = { x: get() { return 1; } }; a.x; a.x; DOM Access Scripted Setter (I only tested .id, so take with a grain of salt-- other properties may differ) var a = { x: set(y) { this.x_ = y; } }; a.x = 1; var a = document.getByElementId(“foo”); a.id;

The Type-Specializing JIT Firefox 3.5+
(Tracemonkey) Chrome 11+ (Crankshaft)

Types FTW! If only JavaScript
had type declarations...

Types FTW! If only JavaScript
had type declarations... ➡ The JIT would know the type of every local variable

Types FTW! If only JavaScript
had type declarations... ➡ The JIT would know the type of every local variable ➡ Know exactly what action to use (no type checks)

Types FTW! If only JavaScript
had type declarations... ➡ The JIT would know the type of every local variable ➡ Know exactly what action to use (no type checks) ➡ Local variables don’t need to be boxed (or unboxed)

Types FTW! If only JavaScript
had type declarations... ➡ The JIT would know the type of every local variable ➡ Know exactly what action to use (no type checks) ➡ Local variables don’t need to be boxed (or unboxed) We call this kind of JIT a type-specializing JIT

But JS doesn’t have types

But JS doesn’t have types
• Problem: JS doesn’t have type declarations • won’t have them any time soon • we don’t want to wait

But JS doesn’t have types
• Problem: JS doesn’t have type declarations • won’t have them any time soon • we don’t want to wait • Solution: run the program for a bit, monitor types

But JS doesn’t have types
• Problem: JS doesn’t have type declarations • won’t have them any time soon • we don’t want to wait • Solution: run the program for a bit, monitor types • Then recompile optimized for those types

Running with the Type-Specializing JIT
Firefox 3.5+ On x = y + z: Chrome 11+ ‣ read the operation x = y + z from memory ‣ read the inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x ‣ write the output x to memory

Running with the Type-Specializing JIT
Firefox 3.5+ On x = y + z: Chrome 11+ ‣ read the operation x = y + z from memory ‣ read the inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x ‣ write the output x to memory

Running with the Type-Specializing JIT
Firefox 3.5+ On x = y + z: Chrome 11+ ‣ read the operation x = y + z from memory ‣ read the inputs y and z from memory ‣ check the types of y and z and choose the action ‣ unbox y and z ‣ execute the action ‣ box the output x ‣ write the output x to memory

Further Optimization 1 Automatic Inlining
original code function getPop(city) { return popdata[city.id]; } for (var i = 0; i < N; ++i) { total += getPop(city); }

Further Optimization 1 Automatic Inlining
original code JIT compiles as if function getPop(city) { you wrote this return popdata[city.id]; } for (var i = 0; i < N; ++i) { total += popdata[city.id]; for (var i = 0; i < N; ++i) { } total += getPop(city); }

Further Optimization 2 Loop Invariant
Code Motion (LICM, “hoisting”) original code for (var i = 0; i < N; ++i) { total += a[i] * (1 + options.tax); }

Further Optimization 2 Loop Invariant
Code Motion (LICM, “hoisting”) original code JIT compiles as if you wrote this for (var i = 0; i < N; ++i) { var f = 1 + options.tax; total += a[i] * for (var i = 0; i < N; ++i) { (1 + options.tax); total += a[i] * f; } }

Optimize Only Hot Code

Optimize Only Hot Code •
Type-specializing JITs can have a hefty startup cost • Need to collect the type information • Advanced compiler optimizations take longer to run

Optimize Only Hot Code •
Type-specializing JITs can have a hefty startup cost • Need to collect the type information • Advanced compiler optimizations take longer to run • Therefore, type specialization is applied selectively • Only on hot code • Tracemonkey: hot = 70 iterations • Crankshaft: hot = according to a profiler • Only if judged to be worthwhile (incomprehensible heuristics)

Current Limitations

Current Limitations • What happens
if the types change after compiling? • Just a few changes -> recompile, slight slowdown • Many changes -> give up and deoptimize to basic JIT

Current Limitations • What happens
if the types change after compiling? • Just a few changes -> recompile, slight slowdown • Many changes -> give up and deoptimize to basic JIT • Array elements, object properties, and closed-over variables • Usually still boxed • Still need to check type and unbox on get, box on set • Typed arrays might help, but support is not always there yet

Current Limitations • What happens
if the types change after compiling? • Just a few changes -> recompile, slight slowdown • Many changes -> give up and deoptimize to basic JIT • Array elements, object properties, and closed-over variables • Usually still boxed • Still need to check type and unbox on get, box on set • Typed arrays might help, but support is not always there yet • JS semantics require overflow checks for integer math

Type Inference for JITs Current
Research @Mozilla

Type Inference

Type Inference • Trying to
get rid of the last few instances of boxing (from before: array and object properties)

Type Inference • Trying to
get rid of the last few instances of boxing (from before: array and object properties) • Idea: use static program analysis to prove types • of object props, array elements, called functions • or, almost prove types, and also prove minimal checks needed

Type Inference Example var a
= []; for (var i = 0; i < N; ++i) { a[i] = i * i; ] var sum = 0; for (var i = 0; i < N; ++i) { sum += a[i]; } Type inference gets this...

Type Inference Example var a
= []; for (var i = 0; i < N; ++i) { a[i] = i * i; ] var sum = 0; for (var i = 0; i < N; ++i) { sum += a[i]; } Type inference gets this... “i is always a number, so i * i is always a number, so a[_] is always a number!”

Type Inference Example var a
= []; var a = []; for (var i = 0; i < N; ++i) { for (var i = 0; i < N; ++i) { a[i] = i * i; if (i % 2) ] a[i] = i * i; else var sum = 0; a[i] = “foo”; for (var i = 0; i < N; ++i) { ] sum += a[i]; } var sum = 0; for (var i = 0; i < N; ++i) { if (i % 2) Type inference gets this... sum += a[i]; } “i is always a number, so i * i is always a number, ...but not this. so a[_] is always a number!”

Type-stable JavaScript The key to
running faster in future JITs is type-stable JavaScript. This means JavaScript where you could declare a single engine-internal type for each variable.

Type-stable JS: examples Type-stable var
g = 34; var o1 = { a: 56 }; var o2 = { a: 99 }; for (var i = 0; i < 10; ++i) { var o = i % 2 ? o1 : o2; g += o.a; } g = 0;

Type-stable JS: examples Type-stable NOT
type-stable var g = 34; var g = 34; var o1 = { a: 56 }; var o1 = { a: 56 }; var o2 = { a: 99 }; var o2 = { z: 22, a: 56 }; for (var i = 0; i < 10; ++i) { for (var i = 0; i < 10; ++i) { var o = i % 2 ? o1 : o2; var o = i % 2 ? o1 : o2; g += o.a; g += o.a; } } g = 0; g = “hello”;

Type-stable JS: examples Type-stable NOT
type-stable var g = 34; var g = 34; var o1 = { a: 56 }; var o1 = { a: 56 }; var o2 = { a: 99 }; var o2 = { z: 22, a: 56 }; for (var i = 0; i < 10; ++i) { for (var i = 0; i < 10; ++i) { var o = i % 2 ? o1 : o2; var o = i % 2 ? o1 : o2; g += o.a; g += o.a; Different shapes } } g = 0; g = “hello”;

Type-stable JS: examples Type-stable NOT
type-stable var g = 34; var g = 34; var o1 = { a: 56 }; var o1 = { a: 56 }; var o2 = { a: 99 }; var o2 = { z: 22, a: 56 }; for (var i = 0; i < 10; ++i) { for (var i = 0; i < 10; ++i) { var o = i % 2 ? o1 : o2; var o = i % 2 ? o1 : o2; g += o.a; g += o.a; Different shapes } } g = 0; g = “hello”; Type change

Garbage Collection

What Allocates Memory? Objects new
Object(); new MyConstructor(); { a: 4, b: 5 } Object.create(); Arrays new Array(); [ 1, 2, 3, 4 ]; Strings new String(“hello”); “<p>” + e.innerHTML + “</p>”

What Allocates Memory? Objects Function
Objects new Object(); var x = function () { ... } new MyConstructor(); new Function(code); { a: 4, b: 5 } Object.create(); Arrays new Array(); [ 1, 2, 3, 4 ]; Strings new String(“hello”); “<p>” + e.innerHTML + “</p>”

What Allocates Memory? Objects Function
Objects new Object(); var x = function () { ... } new MyConstructor(); new Function(code); { a: 4, b: 5 } Object.create(); Arrays Closure Environments new Array(); function outer(name) { [ 1, 2, 3, 4 ]; var x = name; return function inner() { return “Hi, “ + name; Strings } } new String(“hello”); “<p>” + e.innerHTML + “</p>”

What Allocates Memory? Objects Function
Objects new Object(); var x = function () { ... } new MyConstructor(); new Function(code); { a: 4, b: 5 } Object.create(); Arrays Closure Environments new Array(); function outer(name) { [ 1, 2, 3, 4 ]; var x = name; return function inner() { return “Hi, “ + name; Strings } } new String(“hello”); name is stored in an “<p>” + e.innerHTML + “</p>” implicitly created object!

GC Pauses Your Program! Time
JavaScript GC Running Running JS Paused

GC Pauses Your Program! Time
JavaScript GC Running Running JS Paused • Basic GC algorithm (mark and sweep) • Traverse all reachable objects (from locals, window, DOM) • Recycle objects that are not reachable

GC Pauses Your Program! Time
JavaScript GC Running Running JS Paused • Basic GC algorithm (mark and sweep) • Traverse all reachable objects (from locals, window, DOM) • Recycle objects that are not reachable • The JS program is paused during GC for safe traversal

GC Pauses Your Program! Time
JavaScript GC Running Running JS Paused • Basic GC algorithm (mark and sweep) • Traverse all reachable objects (from locals, window, DOM) • Recycle objects that are not reachable • The JS program is paused during GC for safe traversal • Pauses may be long: 100 ms or more • Serious problem for animation • Can also be a drag on general performance

Reducing Pauses with Science 1
Generational GC Chrome

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects Create objects in a frequently collected nursery area

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects Create objects in a frequently collected nursery area Promote long-lived objects to a rarely collected tenured area

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects Create objects in a frequently collected nursery area Promote long-lived objects to a rarely collected tenured area JavaScript GC Running Simple GC Running JS Paused

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects Create objects in a frequently collected nursery area Promote long-lived objects to a rarely collected tenured area JavaScript GC Running Simple GC Running JS Paused JavaScript Generational GC Running

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects Create objects in a frequently collected nursery area Promote long-lived objects to a rarely collected tenured area JavaScript GC Running Simple GC Running JS Paused JavaScript Generational GC Running nursery collection (<100 us)

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects Create objects in a frequently collected nursery area Promote long-lived objects to a rarely collected tenured area JavaScript GC Running Simple GC Running JS Paused JavaScript Generational GC Running tenured collection nursery collection (<100 us)

Reducing Pauses with Science 1
Generational GC Chrome Idea: Optimize for creating many short-lived objects Create objects in a frequently collected nursery area Promote long-lived objects to a rarely collected tenured area JavaScript GC Running Simple GC Running JS Paused JavaScript Generational GC fewer pauses! Running tenured collection nursery collection (<100 us)

Generational GC by Example scavenging
young generation (aka nursery) mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point Line mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point Line a b mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point Line Point a b mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point Line Point Message a b mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point Line Point Message a b mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point Line Point Message Point a b mark-and-sweep tenured generation Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) Point Point Line Point Point a b mark-and-sweep tenured generation Message Message Message Array

Generational GC by Example scavenging
young generation (aka nursery) mark-and-sweep tenured generation Message Message Message Array

Reducing Pauses with Science 1I
Current Incremental GC Research @Mozilla

Reducing Pauses with Science 1I
Current Incremental GC Research @Mozilla Idea: Do a little bit of GC traversal at a time

Reducing Pauses with Science 1I
Current Incremental GC Research @Mozilla Idea: Do a little bit of GC traversal at a time JavaScript GC Running Simple GC Running JS Paused

Reducing Pauses with Science 1I
Current Incremental GC Research @Mozilla Idea: Do a little bit of GC traversal at a time JavaScript GC Running Simple GC Running JS Paused Incremental GC

Reducing Pauses with Science 1I
Current Incremental GC Research @Mozilla Idea: Do a little bit of GC traversal at a time JavaScript GC Running Simple GC Running JS Paused Incremental GC shorter pauses!

Reducing Pauses in Practice

Reducing Pauses in Practice •
For all GCs • Fewer live objects -> shorter pauses (if not incremental), less time spent in GC

Reducing Pauses in Practice •
For all GCs • Fewer live objects -> shorter pauses (if not incremental), less time spent in GC • For simple GCs • Lower allocation rate (objects/second) -> less frequent pauses

Reducing Pauses in Practice •
For all GCs • Fewer live objects -> shorter pauses (if not incremental), less time spent in GC • For simple GCs • Lower allocation rate (objects/second) -> less frequent pauses • For generational GCs • Short-lived objects don’t affect pause frequency • Long-lived objects cost extra (promotion = copying)

JavaScript Engines in Practice

Performance Faults • Performance fault:
when a tiny change hurts performance • Sometimes, just makes one statement slower • Other times, deoptimizes the entire function! • Reasons we have performance faults • bug, tends to get quickly • “rare” case, will get fixed if not rare • hard to optimize, RSN...

Strings

Strings • In the Slow
Zone, but some things are faster than you might think

Strings • In the Slow
Zone, but some things are faster than you might think • .substring() is fast, O(1) • Don’t need to copy characters, just point within original

Strings • In the Slow
Zone, but some things are faster than you might think • .substring() is fast, O(1) • Don’t need to copy characters, just point within original • Concatenation is also optimized • Batch up inputs in a rope or concat tree, concat all at once • Performance fault: prepending (Chrome, Opera)

Strings • In the Slow
Zone, but some things are faster than you might think • .substring() is fast, O(1) // Prepending example var s = “”; •Don’t need to copy characters, just point iwithin<original { for (var = 0; i 100; ++i) s = i + s; • Concatenation is also optimized } • Batch up inputs in a rope or concat tree, concat all at once • Performance fault: prepending (Chrome, Opera)

Arrays fast: dense array var
a = []; Want a fast array? for (var i = 0; i < 100; ++i) { a[i] = 0; ‣ Make sure it’s dense } ‣ 0..N fill or push fill is always dense 3-15x slower: sparse array ‣ Huge gaps are always sparse var a = []; ‣ N..0 fill is sparse on Firefox a[10000] = 0; for (var i = 0; i < 100; ++i) { a[i] = 0; ‣ adding a named property is sparse on Firefox, IE } a.x = 7; // Fx, IE only

Iteration over Arrays fastest: index
iteration // This runs in all in JIT code, // so it’s really fast. for (var i = 0; i < a.length; ++i) { sum += a[i]; }

Iteration over Arrays 3-15x slower:
functional style // This makes N function calls, fastest: index iteration // and most JITs don’t optimize // through C++ reduce(). sum = a.reduce(function(a, b) { // This runs in all in JIT code, return a + b; }); // so it’s really fast. for (var i = 0; i < a.length; ++i) { sum += a[i]; } 20-80x slower: for-in // This calls a C++ function to // navigate the property list. for (var i in a) { sum += a[i]; }

Functions • Function calls use
ICs, so they are fast • Manual inlining can still help sometimes • Key performance faults: • f.call() - 1.3-35x slower than f() • f.apply() - 5-50x slower than f() • arguments - often very slow, but varies

Creating Objects Creating objects is
slow Doesn’t matter too much how you create or populate

Creating Objects Creating objects is
slow Doesn’t matter too much how you create or populate Exception: Constructors on Chrome are fast function Cons(x, y, z) { this.x = x; this.y = y; this.z = z; } for (var i = 0; i < N; ++i) new Cons(i, i + 1, i * 2);

OOP Styling

OOP Styling Prototype function Point(x,
y) { this.x = x; this.y = y; } Point.prototype = { distance: function(pt2) ...

OOP Styling Prototype Information-Hiding function
Point(x, y) { this.x = x; function Point(x, y) { this.y = y; return { } distance: function(pt2) ... Point.prototype = { } distance: function(pt2) ... }

OOP Styling Prototype Information-Hiding function
Point(x, y) { this.x = x; function Point(x, y) { this.y = y; return { } distance: function(pt2) ... Point.prototype = { } distance: function(pt2) ... } Instance Methods function Point(x, y) { this.x = x; this.y = y; this.distance = function(pt2) ... }

OOP Styling Prototype Information-Hiding function
Point(x, y) { this.x = x; function Point(x, y) { this.y = y; return { } distance: function(pt2) ... Point.prototype = { } distance: function(pt2) ... } Prototype style is much faster to create Instance Methods (each closure creates a function object) function Point(x, y) { this.x = x; this.y = y; this.distance = function(pt2) ... }

OOP Styling Prototype Information-Hiding function
Point(x, y) { this.x = x; function Point(x, y) { this.y = y; return { } distance: function(pt2) ... Point.prototype = { } distance: function(pt2) ... } Prototype style is much faster to create Instance Methods (each closure creates a function object) function Point(x, y) { this.x = x; this.y = y; this.distance = function(pt2) ... } Using the objects is about the same

Exceptions • Exceptions assumed to
be rare in perf-sensitive code • running a try statement is free on most browers • throw/catch is really slow • There are many performance faults around exceptions • just having a try statement deoptimizes on some browers • try-finally is perf fault on some

eval and with Short version:
Do not use anywhere near performance sensitive code! Mind-Bogglingly Awful Still Terrible 5-100x slower than using a function call 2-10x slower than without eval var sum = 0; var sum = 0; for (var i = 0; i < N; ++i) { eval(“”); sum = eval(“sum + i”); for (var i = 0; i < N; ++i) { } sum = eval(“sum + i”); }

Top 5 Things to Know

Top 5 Things to Know
5. Avoid eval, with, exceptions near perf-senstive code

Top 5 Things to Know
5. Avoid eval, with, exceptions near perf-senstive code 4. Avoid creating objects in hot loops

Top 5 Things to Know
5. Avoid eval, with, exceptions near perf-senstive code 4. Avoid creating objects in hot loops 3. Use dense arrays (know what causes sparseness)

Top 5 Things to Know
5. Avoid eval, with, exceptions near perf-senstive code 4. Avoid creating objects in hot loops 3. Use dense arrays (know what causes sparseness) 2. Write type-stable code

Top 5 Things to Know
5. Avoid eval, with, exceptions near perf-senstive code 4. Avoid creating objects in hot loops 3. Use dense arrays (know what causes sparseness) 2. Write type-stable code 1. ...

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