Parallel GC and Heap Management in Poly/ML and Isabelle David C.J. Matthews

Parallel GC and Heap Management in Poly/ML and Isabelle David C.J. Matthews David.Matthews@prolingua.co.uk

Summary • Minor GC • Major GC • Sharing pass • Heap sizing

Poly/ML and Isabelle Poly/ML David Matthews Isabelle Larry Paulson Tobias Nipkow Makarius Wenzel

Standard ML Mutable data • Ref • Array • Mutex / Condition variable Immutable data • List • Closure Mostly immutable Most cells have short lifetime Equality of immutables is by value

Minor Collector Values initially allocated in allocation area Copying collector Mutable cells to mutable area Immutable cells to immutable area Only mutable area is scanned for roots

Parallelising Minor Collector Multiple threads process roots Work sharing Lock-free update of forwarding pointers No locking on immutable data Weak coherence

Major GC Mark-sweep Compacting

Parallelising Major GC Lock-free marking Marking is idempotent Sweep phase can operate on separate segments

Sharing phase • Combine cells with same contents • Recursively apply for lists and trees • Quicksort • Parallel • Expensive - O(n log n) • Reduces the live heap size

Heap sizing Paging Live data GC Cost Heap size

Heap sizing: Small Live Data Live data GC Cost Target Heap size

Heap sizing: Large live data Live data GC Cost Target Heap size

Heap sizing • Estimate a cost function • Calculate a minimum • Trigger sharing pass

Parallel Isabelle

JinjaThreads: 64 bit

JinjaThreads: 32 bit

Parallel GC and Heap Management in Poly/ML and Isabelle David C.J. Matthews