ROBERT BOCCHINO, ET AL. UNIVERSAL PARALLEL COMPUTING RESEARCH CENTER UNIVERSITY OF ILLINOIS A Type...

ROBERT BOCCHINO, ET AL .

U N I V E R S A L PA R A L L E L C O M P U T I N G R E SE A R C H C E N T E R

U N I V E R S I T Y O F I L L I N O I S

A Type and Effect System forDeterministic Parallel Java

*Based on OOPSLA-2009 conference presentation by Robert Bocchino

Presented by

Thawan KooburatComputer Science Department

University of Wisconsin - Madison

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Outline

PrologueIntroductionDeterministic Parallel Java (DPJ)Usage PatternsImplementationEvaluation

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Prologue

ParallelArray (Java 7 – java.util.concurrent) Slice up data into blocks Perform operation on all data concurrently

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Prologue

ParallelArray of distinct objects

Framework cannot prevent programmer from writing code will

break the semantic

Access global variables

Time

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Introduction

Deterministic Execution Same input always produce same output Many computational algorithms are deterministic

Many programs use parallel execution in order to gain performance , but it is not part of the specification.

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Deterministic-by-default

Guaranteed deterministic execution by default

Nondeterministic behavior must be explicitly requested. foreach

Iterating over independent objects foreach_nd

Iterating over overlapping objects

R. Bocchino, V. Adve, S. Adve, and M. Snir, “Parallel Programming Must Be Deterministic by Default”

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Benefits

Can reason sequentiallyNo hidden parallel bugs Testing based on input

No need to test all interleaving combinationsParallelize incrementally Easier to compose

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Deterministic Parallel Java (DPJ)

Based on Java languageFork/Join parallelism

Cobegin Foreach

Type and effect system Expose noninterference (Soundness) Field-level granularity Differentiate between readers and writers

Guarantee deterministic execution at compile time

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Regions and Effects

Regions Divide memory location into regions Can be formed into a tree

class TreeNode<region P> { region L, R, V; int value in V; TreeNode<L> left = new TreeNode<L>(); TreeNode<R> right = new TreeNode<R>();}

Parameterized by region

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Regions

Root

Root:L Root:R

Root:L:L

Root:L:R

Root:R:L

Root:R:R

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Effects

Effects Read or write operations on data Programmer specify effect summary for each method

class TreeNode<region P> { ... TreeNode<L> left = new TreeNode<L>(); TreeNode<R> right = new TreeNode<R>(); void updateChildren() writes L, R { cobegin { left.data = 0; /* writes L */ right.data = 1; /* writes R */ } }

Method effect summary

Compiler inferred from type

Non interferenc

e

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Usage Patterns

Region path lists (RPLs) Updating nested data structure with field-granularity

Index-parameterized array Updating an array of objects

Subarray Partition array for divide and conquer pattern.

Commutativity Declare effect summary based on operation’s

semantic

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Region Path Lists (RPLs)

class Tree<region P> { region L, R; int value in P; Tree<P:L> left = new Tree<P:L>(); Tree<P:R> right = new Tree<P:R>();}

P= Rootvalu

eRoot

left Root:Lright Root:R

P=Root:Lvalu

eRoot:L

left Root:L:Lright Root:L:R

P=Root:Rvalu

eRoot:R

left Root:R:Lright Root:R:R

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Region Path Lists (RPLs)

class Tree<region P> { ... int increment() writes P:* { value++; /* writes P */ cobegin { /* writes P:L:* */ if (left != null) left.increment(); /* writes P:R:* */ if (right != null) right.increment(); }}

P:L:* ⊆ P:* P:R:* ⊆ P:*

Inclusion(Method effect)

Disjointness(Cobegin

body)

P:L:* ∩ P:R:* = ∅

Method effect summary

Effect inferred from type and summary

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Index-parameterized Array

Enforce disjointness of array’s element (reference)

Syntax: C<[i]>[]#i

1 2 3 4 1 2 3 4

a[i] b[i]

C<[1]> C<[2]> C<[3]> C<[4]>

1 2 3 4c[i]

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Index-parameterized Array

final Body<[_]>[]<[_] > bodies = new Body<[_]>[N]<[_]>;foreach (int i in 0, N) { /* writes [i] */ bodies[i] = new Body<[i]> ();}foreach (int i in 0, N) { /* reads [i], Link, *:M writes [i]:F */ bodies[i].computeForce();

class Body<region P> { double mass in P:M; double force in P:F; Body <*> link in Link; void computeForce() reads Link, *:M writes P:F {..}}

Write to each element is distinct

Read does not interfere write

Objects are parameterlized by index region

Operations in foreach block is noninterference

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Subarray

Mechanisms: DPJ Libraries DPJArray: Wrapper class for Java array DPJPartition: Collections of disjoint DPJArray

Divide and Conquer usage pattern Initialize an array using DPJArray Recursively partition original array using DPJPartition

Each partition is a disjoint subset of original array Create a tree of partition based on flat array

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Subarray

static <region R> void quicksort(DPJArray<R> A) writes R:* { int p = quicksortPartition(A); /* Chop array into two disjoint pieces */ final DPJPartition<R> segs = new DPJPartition<R>(A, p, OPEN); cobegin { /* write segs:[0]:* */ quicksort(segs.get(0)); /* write segs:[1]:* */ quicksort(segs.get(1)); }}

Use local variable to represent regions

RDPJArray

segs[0] segs[1]pDPJPartition

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Commutativity

Method annotation

Allow programmers to override effect system Compiler will not check inside the method

This allows cobegin { add(e1); add(e2); } Any order of operations is equivalent Operation is atomic

interface Set<type T, region R> { commutative void add(T e) writes R;}

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Commutativity

Method invocation

foreach (int i in 0, n) { /* invokes Set.add with writes R */ set.add(A[i]);}

cobegin { /* invokes Set.add with writes R */ set.add(A); /* invokes Set.size with read R */ set.size();}

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Implementation

Extend Sun’s javac compiler Covert DPJ into normal Java source

Compile to ForkJoinTask Framework (Java7) Similar to Cilk DPJ translates foreach and cobegin to tasks

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Evaluation

Benchmarks

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Performance

4

8

12

16

20

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4 8 12 16 20 24

Sp

eed

up

Number of cores

Barnes-HutMergesortIDEAK-MeansCollision TreeMonte Carlo

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Q/A