A Type and Effect System for Deterministic Parallel Java
This presentation explores the Type and Effect System for Deterministic Parallel Java (DPJ) developed by Robert Bocchino and others at the University of Illinois. Detailing its implementation, usage patterns, and evaluation, it highlights the benefits of deterministic execution by default, facilitating easier reasoning and testing in parallel algorithms. The framework emphasizes methods for parallelizing operations while guaranteeing no hidden concurrency bugs. Key features include handling global variables, managing memory regions, and specifying method effects, all to ensure soundness and predictability in parallel programming.
A Type and Effect System for Deterministic Parallel Java
E N D
Presentation Transcript
A Type and Effect System forDeterministic Parallel Java Robert Bocchino, et al. Universal Parallel Computing Research Center University of Illinois Presented by Thawan Kooburat Computer Science Department University of Wisconsin - Madison *Based on OOPSLA-2009 conference presentation by Robert Bocchino
Outline Prologue Introduction Deterministic Parallel Java (DPJ) Usage Patterns Implementation Evaluation
Prologue • ParallelArray (Java 7 – java.util.concurrent) • Slice up data into blocks • Perform operation on all data concurrently
Prologue ParallelArray of distinct objects Time Access global variables Framework cannot prevent programmer from writing code will break the semantic
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.
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”
Benefits • Can reason sequentially • No hidden parallel bugs • Testing based on input • No need to test all interleaving combinations • Parallelize incrementally • Easier to compose
Deterministic Parallel Java (DPJ) • Based on Java language • Fork/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
Regions and Effects • Regions • Divide memory location into regions • Can be formed into a tree Parameterized by region class TreeNode<region P> { region L, R, V; int value in V; TreeNode<L> left = new TreeNode<L>(); TreeNode<R> right = new TreeNode<R>(); }
Regions Root Root:L Root:R Root:L:L Root:L:R Root:R:L Root:R:R
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() writesL, R { cobegin { left.data = 0; /* writesL*/ right.data = 1; /* writesR*/ } } Method effect summary Non interference Compiler inferred from type
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
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= Root value Root left Root:L right Root:R P=Root:L P=Root:R value Root:L value Root:R left Root:L:L left Root:R:L right Root:L:R right Root:R:R
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(); } } Method effect summary Effect inferred from type and summary Inclusion (Method effect) P:L:* ⊆ P:* P:R:* ⊆ P:* Disjointness (Cobegin body) P:L:* ∩ P:R:* = ∅
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] 1 2 3 4 c[i] C<[1]> C<[2]> C<[3]> C<[4]>
Index-parameterized Array class Body<region P> { double mass in P:M; double force in P:F; Body <*> link in Link; void computeForce() readsLink, *:Mwrites P:F {..} } final Body<[_]>[]<[_] > bodies = new Body<[_]>[N]<[_]>; foreach (inti in 0, N) { /* writes [i] */ bodies[i] = new Body<[i]> (); } foreach (inti in 0, N) { /* reads [i], Link, *:Mwrites [i]:F */ bodies[i].computeForce(); Objects are parameterlized by index region Write to each element is distinct Operations in foreach block is noninterference Read does not interfere write
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
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 R DPJArray segs[0] p segs[1] DPJPartition
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; }
Commutativity Method invocation foreach (inti 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(); }
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
Evaluation Benchmarks
Performance 24 Barnes-Hut Mergesort IDEA K-Means Collision Tree Monte Carlo 20 Speedup 16 12 8 4 4 8 12 16 20 24 Number of cores