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

2. Summary
Minor GC
Major GC
Sharing pass
Heap sizing

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

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

5. 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

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

7. Major GC
Mark-sweep
Compacting

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

9. 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

10. Heap sizing
Paging
Live data
GC Cost
Heap size

11. Heap sizing: Small Live Data
GC Cost
Target
Heap size

12. Heap sizing: Large live data
GC Cost
Target
Heap size

13. Heap sizing Estimate a cost function Calculate a minimum
Trigger sharing pass

14. Parallel Isabelle

15. JinjaThreads: 64 bit

16. JinjaThreads: 32 bit