Concurrent Message Processing using Transactional
Memory in the Actor ModelWTM 2013
Pascal Felber, Derin Harmanci, Yaroslav Hayduk and Anita Sobe
Yaroslav Hayduk 2
The Actor Model
• Hewitt & Baker - „Laws for Communicating Parallel Processes“
• Motivated by the prospect of highly parallel computing machines with many microprocessors + own local memory
Yaroslav Hayduk 3
The Actor Model – basic principles
• everything is an actor (VS an object)• asynchronous message passing• has access to its local state only • strong encapsulation• inherently concurrent
Yaroslav Hayduk 4
OOP and Actors: Communication
Object A Object B
Actor A Object B
ObjectB.publicField=10ObjectB.publicMethod()
ActorA [SendMessageTo] ActorB
VS
asynchronous message passing
direct access
5
Essential Actor properties
• Processes one message at a time– Yey! No race conditions or other hazards
• No (access to) shared state • Can send messages to other actors only• Switch its behavior
Yaroslav Hayduk
6
Behind the (Actor) scenes
Yaroslav Hayduk
Mailbox…Contains 2 Insert 3
2 5 6 8 9
Local Actor state
In progress:Contains 8
C
A
B
A “List” Actor
Remove 9
Yaroslav Hayduk 7
Main issues
1.The processing of one message at a time
Yaroslav Hayduk 8
Notable Related Work
• Scholliers et al. – Parallel Actor Monitors– does not use STM for processing messages
concurrently• Shams et al. – Habanero Scala– async-finish programming model– processes parts of one message (and not many
messages) concurrently
Yaroslav Hayduk 9
Idea:
Process multiple messages concurrently
• Problem: the list can be easily corrupted• Solution: Wrap each message processing in an
STM transaction. When conflicts happen, (roll back and) repeat the message processing
Yaroslav Hayduk 10
Concurrent message processing
Actor Mailbox…Contains 2 Insert 3
2 5 6 8 9
Local Actor state
A “List” Actor
Messages In progress
Contains 6
Insert 12
… Insert 12
Each message is processed in a transaction
11
Coordinated Transactions
Yaroslav Hayduk
A
A List Range (1..25) Actor
Global list sum
A List Range (100..125) Actor
……….
Yaroslav Hayduk 12
Local Actor Sum: Zoom-in
2 5 6 8 9
Local Actor state
A List Range Actor
Messages In progress
1. Calculate local sum2. Forward new partial sum3. Block (for consistency)
New partial sumPrev partial sum
Yaroslav Hayduk 13
Main issues
2.Extensive blocking of actors involved in a
coordinated transaction
Yaroslav Hayduk 14
Idea:
Remove blocking; process other messages speculatively
• Pre-commit the local coordinated transaction• Process other messages in a transaction
speculatively
Yaroslav Hayduk 15
Non-blocking coordinated transactions
2 5 6 8 9
Local Actor state
A List Range Actor
Messages In progress
Saved: Partially committed local coordinated transaction
Actor Mailbox…Contains 2 List sum
Speculatively process:Insert 3
Yaroslav Hayduk 16
Evaluation
50 100 250 500 750 10000
10000
20000
30000
40000
50000
60000
List Actors = 8, Writes = 98%, Sum = 1%
Regular Concurrent Coordinated
Request Actors
Mill
is
Yaroslav Hayduk 17
Evaluation
50 100 250 500 750 10000
10000
20000
30000
40000
50000
60000
70000
List Actors = 16, Writes = 98%, Sum = 1%
Regular Concurrent Coordinated
Request Actors
Mill
is
Yaroslav Hayduk 18
Summary
• By using speculation, we can achieve a higher message throughput in the Actor Model
• By using STM we guarantee that the Actor’s state is never corrupted
Thank you Questions?
