COORDINATION'16

ParT types presentation given at COORDINATION'16

Transcript

1. PART: AN ASYNCHRONOUS PARALLEL ABSTRACTION FOR SPECULATIVE PIPELINE COMPUTATIONS Kiko Fernandez-Reyes, Dave Clarke and Daniel S.McCain Uppsala University, Sweden
2. PART: AN ASYNCHRONOUS PARALLEL ABSTRACTION FOR SPECULATIVE PIPELINE COMPUTATIONS Asynchronous: Don’t stop the world
3. PART: AN ASYNCHRONOUS PARALLEL ABSTRACTION FOR SPECULATIVE PIPELINE COMPUTATIONS Asynchronous: Don’t stop the world Parallel: manycore era
4. PART: AN ASYNCHRONOUS PARALLEL ABSTRACTION FOR SPECULATIVE PIPELINE COMPUTATIONS Asynchronous: Don’t stop the world Parallel Abstraction: manycore era + parallel collection
5. PART: AN ASYNCHRONOUS PARALLEL ABSTRACTION FOR SPECULATIVE PIPELINE COMPUTATIONS Asynchronous: Don’t stop the world Parallel Abstraction: manycore era + parallel collection Speculative: kill-off computations Better use for CPU
6. PART: AN ASYNCHRONOUS PARALLEL ABSTRACTION FOR SPECULATIVE PIPELINE COMPUTATIONS Asynchronous: Don’t stop the world Parallel Abstraction: manycore era + parallel collection Speculative: kill-off computations Better use of CPU Pipeline: highly parallelizable
7. Motivation Encore Programming Language: • Asynchronous • Parallel • Futures as synchronisation point 1
8. Motivation Encore Programming Language: • Asynchronous • Parallel • Futures as synchronisation point Actors & Tasks 1
9. Tasks calculateF ƒ1 get ƒ1 (Block until future is fulfilled) return Maybe(bool) 1. 2. 3. 4. Steps: 2 let fut : Fut(Maybe bool) = async { calculateF(f, a); } in return get(fut) (get :: Fut t → t)
10. Tasks 3 let fut : Maybe bool = async { calculateF(f, a); } in fut ⤳ (\(m: Maybe bool) -> match m with Just true => a …) calculateF ƒ1 1. 2. Steps: ƒ1 ⤳ (\(m: Maybe bool) -> match m with … ƒ2 = ⤳ :: Fut t → (t → t’) → Fut t’
11. Motivation Encore Programming Language: • Asynchronous • Parallel • Futures as synchronisation point Actors & Tasks 4
12. Motivation Encore Programming Language: • Asynchronous • Parallel • Futures as synchronisation point Actors & Tasks Actors and tasks lack of an abstraction for the asynchronous and parallel nature of their computations 4
13. Motivation 5 Parallel Portfolio-based SAT solver Goal: is a Formula satisfiable or not? Input: Array of Strategies, Formula Output: Maybe Assignment
14. Motivation 6 Parallel Portfolio-based SAT solver foreach s: strategies async solve(formula, s, new Assignment())
15. Motivation 6 Parallel Portfolio-based SAT solver foreach s: strategies async solve(formula, s, new Assignment()) Futures
16. Motivation 6 Parallel Portfolio-based SAT solver foreach s: strategies async solve(formula, s, new Assignment()) Futures Asynchronously continue running
17. Motivation 6 Parallel Portfolio-based SAT solver foreach s: strategies async solve(formula, s, new Assignment()) Futures Asynchronously continue running How can I select the first one that finishes?
18. Motivation 7 Parallel Portfolio-based SAT solver solve solve solve
19. Motivation 7 Parallel Portfolio-based SAT solver solve solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula
20. Motivation 7 Parallel Portfolio-based SAT solver solve solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula async
21. Motivation 7 Parallel Portfolio-based SAT solver solve solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula async async
22. Motivation 7 Parallel Portfolio-based SAT solver solve solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula EvalFormula async async
23. Motivation 7 Parallel Portfolio-based SAT solver solve EvalFormula solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula EvalFormula async async
24. Motivation 7 Parallel Portfolio-based SAT solver solve EvalFormula solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula EvalFormula ⤳ satisfiable? async async
25. Motivation 8 EvalFormula solve solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula EvalFormula ⤳ satisfiable? async async Parallel Portfolio-based SAT solver ⤳ satisfiable?
26. Motivation 8 EvalFormula solve solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula EvalFormula ⤳ satisfiable? Don’t know solve async async Parallel Portfolio-based SAT solver ⤳ satisfiable?
27. Motivation 8 EvalFormula solve solve solve Strategy 1. Take Variable 2. Split variable 3. Evaluate formula EvalFormula False ⤳ satisfiable? Don’t know solve async async Parallel Portfolio-based SAT solver ⤳ satisfiable?
28. Motivation 9
29. Motivation 9
30. Motivation 9
31. Motivation 9
32. Motivation 9 value ƒ2 ƒ1 ƒ3 ƒ2
33. Motivation 10 value ƒ2 ƒ1 ƒ3 ƒ2
34. Motivation 10 value ƒ2 ƒ1 ƒ3 ƒ2
35. Motivation 10 value ƒ2 ƒ1 ƒ3 ƒ2
36. Motivation 10 value ƒ2 ƒ1 ƒ3 ƒ2 ƒ1
37. Motivation 10 value ƒ2 ƒ1 ƒ3 ƒ2 ƒ1 true
38. Motivation 10 value ƒ2 ƒ1 ƒ3 ƒ2 ƒ1 true
39. Motivation 11 ƒ1 ƒ3 ƒ1 true value ƒ2 ƒ2
40. Motivation 11 ƒ1 ƒ3 ƒ1 true
41. Motivation 11 ƒ1 ƒ1 true
42. Contributions • Parallel abstraction for handling complex coordination patterns • Asynchronous Combinators • Kills-off speculative computations when no longer needed • Prototypes in Encore and Clojure 12
43. Index • ParT & Combinators • Example: Parallel Portfolio-based SAT solver • Implementation: under the hood • Future work & Limitations • Conclusion 19
44. ParT & Combinators 13 Functional data structure Encapsulates parallel & asynchronous computations Controlled via parallel combinators derived from Orc… typed & asynchronous async computation async computation async computation ParT
45. ParT & Combinators 13 Functional data structure Encapsulates parallel & asynchronous computations Controlled via parallel combinators derived from Orc… typed & asynchronous async computation async computation async computation ParT
46. ParT & Combinators 13 Functional data structure Encapsulates parallel & asynchronous computations Controlled via parallel combinators derived from Orc… typed & asynchronous async computation async computation async computation ParT Handle to ongoing parallel computations
47. Example • SAT solver • Multiple strategies • Pipeline and Speculative parallelism 14
48. Example: SAT solver Formula [Strategies] 15
49. Example: SAT solver Formula [Strategies] s1 s2 sn 15 each
50. Example: SAT solver Formula [Strategies] s1 s2 sn solve 15 each
51. Example: SAT solver Formula [Strategies] s1 s2 sn solve Strategy 1. Take variable 2. Split variable 15 each
52. Example: SAT solver olve Strategy 1. Take variable 2. Split variable 16
53. Example: SAT solver olve Strategy 1. Take variable 2. Split variable evalFormula evalFormula 16 ||
54. Example: SAT solver olve Strategy 1. Take variable 2. Split variable evalFormula evalFormula 16 || doesn’t spawn new asynchronous computations! It rather declares there is possibility for parallelism ||
55. Example: SAT solver olve Strategy 1. Take variable 2. Split variable evalFormula evalFormula 16 || doesn’t spawn new asynchronous computations! It rather declares there is possibility for parallelism || >>= >>= satisfiable? satisfiable?
56. Example: SAT solver Formula [Strategies] s1 s2 sn 17
57. Example: SAT solver Formula [Strategies] s1 s2 sn formula not solved 17
58. Example: SAT solver Formula [Strategies] s1 s2 sn formula not solved false x 17
59. Example: SAT solver Formula [Strategies] s1 s2 sn formula not solved false true x 17
60. Example: SAT solver Formula [Strategies] s1 s2 sn true 18
61. Example: SAT solver Formula [Strategies] s1 s2 sn true 18
62. Example: SAT solver Formula [Strategies] s1 s2 sn true 18
63. Example: SAT solver Formula [Strategies] s1 s2 sn true 18
64. Example: SAT solver Formula [Strategies] s1 s2 sn true 18
65. Example: SAT solver Formula [Strategies] s1 s2 sn true 19
66. Example: SAT solver Formula [Strategies] s1 s2 sn true 19
67. Example: SAT solver Formula [Strategies] 20
68. Example: SAT solver Formula [Strategies] 20 ParT
69. Example: SAT solver Formula [Strategies] 20 ParT
70. Example: SAT solver Formula [Strategies] << 20 ParT
71. Example: SAT solver Formula [Strategies] << Computation 20 ParT
72. Example: SAT solver Formula [Strategies] << Computation Parallel and Asynchronous computations captured in the ParT abstraction This computation can start immediately 21
73. ParT Example: SAT solver Formula [Strategies] << Computation Parallel and Asynchronous computations captured in the ParT abstraction This computation can start immediately 21
74. Example: SAT solver << fut2Par << (each(sts) >>= \(s: Strategy) -> (async sat(s, fml, new Assignment())✝)) 22 ParT Computation
75. Example: SAT solver << fut2Par << (each(sts) >>= \(s: Strategy) -> (async sat(s, fml, new Assignment())✝)) 22 ParT Computation
76. Example: SAT solver << fut2Par << (each(sts) >>= \(s: Strategy) -> (async sat(s, fml, new Assignment())✝)) 22 ParT Computation
77. Implementation • Futures are essential to ParT • Futures are handles to single parallel computations • ParT are handle to collection of parallel computations 23
78. Implementation ( )✝ :: Fut (Par t) → Par t ( ) :: Fut t → Par t ⚬ { v } :: t → Par t ƒParT LIFT 24 ƒ1 VALUE
79. Par Implementation ( )✝ :: Fut (Par t) → Par t ( ) :: Fut t → Par t ⚬ { v } :: t → Par t ƒParT LIFT 24 Par Par ƒ1 VALUE
80. Implementation >> :: Par t → (t → t’) → Par t’ ParT ƒ1 >> function ParT ƒ2 = SEQUENCE 25
81. Implementation >> :: Par t → (t → t’) → Par t’ ParT ƒ1 >> function ParT ƒ2 ƒ1 ⤳ = SEQUENCE 25 =
82. Implementation >> :: Par t → (t → t’) → Par t’ ParT ƒ1 >> function ParT ƒ2 ƒ1 ⤳ = ParT >> function ParT = VALUE VALUE’ SEQUENCE 25 =
83. Combinators << :: (Fut(Maybe t) → Par t’) → Par t→ Par t’ ƒ1 → → ƒ2 → function Par t’ ParT << VALUE PRUNE 33
84. Combinators << :: (Fut(Maybe t) → Par t’) → Par t→ Par t’ ƒ1 → → ƒ2 → function Par t’ ParT << VALUE PRUNE 33
85. Combinators << :: (Fut(Maybe t) → Par t’) → Par t→ Par t’ ƒ1 → → ƒ2 → function Par t’ ParT << VALUE PRUNE 33
86. Combinators << :: (Fut(Maybe t) → Par t’) → Par t→ Par t’ ƒ1 → function Par t’ ParT << VALUE PRUNE 33
87. Combinators << :: (Fut(Maybe t) → Par t’) → Par t→ Par t’ ƒ1 → function Par t’ ParT << VALUE PRUNE 33 ParT
88. Combinators << :: (Fut(Maybe t) → Par t’) → Par t→ Par t’ ƒ1 → function Par t’ ParT << VALUE PRUNE 33 ParT
89. Future work & Limitations • Limitation: Computations must be side-effect free • Integration with actors possible via software transactional memory • Adding more combinators • Improving the current implementation 26
90. Conclusions • ParT: abstraction to handle parallel and async computations • Non-blocking combinators • Tracks down and kills-off speculative work 27
91. Questions 28