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Locality-Conscious Lock-Free Linked Lists. Anastasia Braginsky & Erez Petrank. Lock-Free Locality-Conscious Linked Lists. List of constant size '' containers " , with minimal and maximal bounds on the number of elements in container Traverse the list quickly to the relevant container
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Locality-Conscious Lock-Free Linked Lists Anastasia Braginsky & ErezPetrank
Lock-Free Locality-Conscious Linked Lists • List of constant size ''containers", with minimal and maximal bounds on the number of elements in container • Traverse the list quickly to the relevant container • Lock-free, locality-conscious, fast access, scalable 3 7 9 12 18 25 26 31 40 52 63 77 89 92
Non-blocking Algorithms • Ensures progress in finite number of steps. • A non-blocking algorithm is: • wait-free if there is a guaranteed per-thread progress in bounded number of steps • lock-free if there is a guaranteed system-wide progress in bounded number of steps • obstruction-free if a single thread executing in isolation for a bounded number of steps will make progress.
Existing Lock-Free Lists Designs • J. D. VALOIS, Lock-free linked lists using compare-and-swap, in Proc. PODC, 1995. • T.L. HARRIS, A pragmatic implementation of non-blocking linked-lists, in DISC 2001. • M.M. MICHAEL, Hazard Pointers: Safe Memory Reclamation for Lock-Free Objects, in IEEE 2004. • M. FORMITCHEV, and E. RUPERT. Lock-free linked lists and skip lists, in Proc. PODC, 2004.
Outline • Introduction • A list of memory chunks • Design of in-chunk list • Merges & Splits via freezing • Empirical results • Summary
The List Structure • A list consists of • A list of memory chunks • A list in each chunk (chunk implementation) • When a chunk gets too sparse or dense, the update operations on the list are stopped and the chunk is split or merged with its preceding chunk.
An Example of a List of Fixed-Sized Memory Chunks NULL HEAD NextChunk NextChunk Chunk B Chunk A EntriesHead EntriesHead Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A Key: 3 Data: G Key: 14 Data: K
When No More Space for Insertion NULL HEAD Freeze NextChunk NextChunk Chunk B Chunk A EntriesHead EntriesHead Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A Key: 3 Data: G Key: 6 Data: B Key: 14 Data: K Key: 9 Data: C Key: 12 Data: H
Split NULL HEAD Freeze NextChunk NextChunk Chunk B Chunk A EntriesHead EntriesHead Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A Key: 3 Data: G Key: 6 Data: B Key: 14 Data: K Key: 9 Data: C Key: 12 Data: H NextChunk NextChunk Chunk C Chunk D EntriesHead EntriesHead Key: 3 Data: G Key: 6 Data: B Key: 9 Data: C Key: 14 Data: K Key: 12 Data: H
Split NULL HEAD Freeze NextChunk NextChunk Chunk B Chunk A EntriesHead EntriesHead Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A Key: 3 Data: G Key: 6 Data: B Key: 14 Data: K Key: 9 Data: C Key: 12 Data: H NextChunk NextChunk Chunk C Chunk D EntriesHead EntriesHead Key: 3 Data: G Key: 6 Data: B Key: 9 Data: C Key: 14 Data: K Key: 12 Data: H
When a Chunk Gets Sparse NULL HEAD Freeze slave NextChunk NextChunk Chunk C Chunk B EntriesHead EntriesHead Key: 3 Data: G Key: 6 Data: B Key: 9 Data: C Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A NextChunk Chunk D EntriesHead Key: 14 Data: K Freeze master
Merge NULL HEAD Freeze slave NextChunk NextChunk Chunk C Chunk B EntriesHead EntriesHead Key: 3 Data: G Key: 6 Data: B Key: 9 Data: C Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A NextChunk Chunk E NextChunk Chunk D EntriesHead EntriesHead Key: 3 Data: G Key: 6 Data: B Key: 14 Data: K Key: 9 Data: C Key: 14 Data: K Freeze master
Merge NULL HEAD Freeze slave NextChunk NextChunk Chunk C Chunk B EntriesHead EntriesHead Key: 3 Data: G Key: 6 Data: B Key: 9 Data: C Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A NextChunk Chunk E NextChunk Chunk D EntriesHead EntriesHead Key: 3 Data: G Key: 6 Data: B Key: 14 Data: K Key: 9 Data: C Key: 14 Data: K Freeze master
Outline • Introduction • A list of memory chunks • Design of in-chunk list • Merges & Splits via freezing • Empirical results • Summary
A List of Fixed-Sized Memory Chunks HEAD NULL NextChunk NextChunk Chunk B Chunk A EntriesHead EntriesHead Key: 89 Data: M Key: 67 Data: D Key: 25 Data: A Key: 3 Data: G Key: 14 Data: K
The Structure of an Entry • 2 machine words • Freeze bit: to mark chunk entries frozen. • A ┴ (bottom) value is not allowed as a key value. It means that entry is not allocated. Data Key Freeze bit Next entry pointer Delete bit Freeze bit 32 bit 31 bit 62 bit KeyData word NextEntry word
The Structure of a Chunk Head: dummy entry Counter: 4 new pointer Merge Buddy pointer Freeze State 2 bits NextChunk pointer Key: ┴ Key: 7 Data: 89 Key: 14 Data: 9 Key: ┴ Key: 22 Data: 13 Key: 24 Data: 78 Deleted bit: 1 Key: ┴ Key: 23 Data: 53 Deleted bit: 1 Key: 11 Data: 13 An array of entries of size MAX
Initiating a Freeze • When a process p realizes that • A chunk is full, or • A chunk is sparse, or • A chunk is in progress of being frozen, • Then p starts a freeze or p helps another process that has already started a freeze.
The Freeze Process Starts by: • Going over all the entries in the array and setting their freeze bit • Finish • insertions of all currently allocated entries that are not yet in the list • deletions of entries already marked as deleted but still in the list
Chunk List is Different from Known Lock-Free Linked Lists • Non-private insertion: entry is visible when allocated, even before linking to the list. • Allow help with insertion. • Boundary conditions causing merges and splits.
Entry Allocation k:3 d:9 f:1 k:4 d:2 f:1 k:┴ d:0 f:1 k:8 d:5 f:0 k:┴ d:0 f:0 • Entry is allocated at the beginning of the insertion process • Find zeroed entry, with ┴ key value • Allocate by swapping the KeyData word to the desired value. • Upon a failure of the CAS command, goto 2. • Frozen entry can not be allocated • If no entry is found -- freeze starts • Next, use allocated entry for list insertion…
Entry Allocation k:3 d:9 f:1 k:4 d:2 f:1 k:┴ d:0 f:1 k:8 d:5 f:0 k:6 d:2 f:0 • Entry is allocated at the beginning of the insertion process • Find zeroed entry, with ┴ key value • Allocate by swapping the KeyData word to the desired value. • Upon a failure of the CAS command, goto 2. • Frozen entry can not be allocated • If no entry is found -- freeze starts • Next, use allocated entry for list insertion…
Insertion Algorithm previous next k:3 d:9 f:1 k:4 d:2 f:1 k:┴ d:0 f:1 k:8 d:5 f:0 k:6 d:2 f:0 • Record entry’s next pointer value in savedNext. • Find a location for adding the new entry. • If key already exists (in a different entry) – free allocated entry by clearing it and return. • CAS entry’s next pointer from savedNext to the next entry in the list • CAS previous entry’s next pointer to newly allocated entry • If any CAS fails, goto 1 (restarting from the beginning of a chunk) • Increase the counter and return
Insertion Algorithm previous next k:3 d:9 f:1 k:4 d:2 f:1 k:┴ d:0 f:1 k:8 d:5 f:0 k:6 d:2 f:0 • Record entry’s next pointer value in savedNext. • Find a location for adding the new entry. • If key already exists (in a different entry) – free allocated entry by clearing it and return. • CAS entry’s next pointer from savedNext to the next entry in the list • CAS previous entry’s next pointer to newly allocated entry • If any CAS fails, goto 1 (restarting from the beginning of a chunk) • Increase the counter and return
Insertion Algorithm previous next k:3 d:9 f:1 k:4 d:2 f:1 k:┴ d:0 f:1 k:8 d:5 f:0 k:6 d:2 f:0 • Record entry’s next pointer value in savedNext. • Find a location for adding the new entry. • If key already exists (in a different entry) – free allocated entry by clearing it and return. • CAS entry’s next pointer from savedNext to the next entry in the list • CAS previous entry’s next pointer to newly allocated entry • If any CAS fails, goto 1 (restarting from the beginning of a chunk) • Increase the counter and return
Deletion • Standard implementation, except for taking care not to get under the minimum number of entries • Counter always holds a lower bound on the actual number of entries. • increased after actual insert • decreased before actual delete • Decrementing the counter below the minimum allowed number, initiates a freeze • Frozen entry can not be marked as deleted
Outline • Introduction • A list of memory chunks • Design of in-chunk list • Merges & Splits via freezing • Empirical results • Summary
Freezing • Phase I: Marking entries with frozen bits • Non-frozen entries can still change concurrently • Phase II: List stabilization • Everything frozen, now finish all incomplete operations. • Phase III: Decision • Split, merge, or copy. • Phase IV: Recovery • Implementation of the above decision
Phase IV - Recovery • Allocate new chunk or chunks locally • Copy the frozen data to the new chunk • Execute the operation that initially caused the freeze • Attach the new chunk to the frozen one • Replace frozen chunk(s) with new chunk(s) in the entire List’s data structure
Remarks • Search can run on a frozen chunk (and is not delayed). • Wait-free except for the use of the hazard pointer mechanism • A chunk can never be unfrozen
Outline • Introduction • A list of memory chunks • Design of in-chunk list • Merges & Splits via freezing • Empirical results • Summary
The Test Environment • Platform: SUN FIRE with UltraSPARC T1 8-core processor, each core running 4 hyper-threads. • OS: Solaris 10 • Chunk size set to virtual page size -- 8KB. • All accesses inside a chunk are on the same page
Workload • Each test had two stages: • Stage I: • Insertions (only) of N random keys (in order to obtain a substantial list) • N: 103, 104, 105, 106 • Stage II: • Insertions, deletions and searches in parallel • N operations overall out of which 15% insertions, 15% deletions, and 70% searches. • Reporting results for runs of 32 concurrent threads.
Reference for Comparison • Michael’s lock-free linked list implemented in C according to the pseudo-code from • MICHAEL, M. M., Hazard Pointers: Safe Memory Reclamation for Lock-Free Objects., in IEEE 2004. • Uses hazard pointers. • A Java implementation of the lock-free linked list provided in the book “The Art of Multiprocessor Programming” • Garbage collection is assumed.
Comparison with Michael’s ListTotal Time Constantly better performance. For substantial lists in more then 10 times Already at 20000 we get same performance More then 10 times faster
Comparison with Michael’s ListSingle Operation Average Better performance, as lists are going more substantial Again constantly better performance
Comparison with Lock-Free List in Java Single Operation Average
Outline • Introduction • A list of memory chunks • Design of in-chunk list • Merges & Splits via freezing • Empirical results • Summary
Conclusion • New lock-free algorithm for chunked linked list • Fast due to: • Skips over chunks • Restarting from the beginning of a chunk • Locality-conscious • May be useful for other structures that can use the chunks • Good empirical results for the substantial lists