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Practical Assignment Sinking for Dynamic Compilers

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Presentation on theme: "Practical Assignment Sinking for Dynamic Compilers"— Presentation transcript:

1 Practical Assignment Sinking for Dynamic Compilers
Reid Copeland, Mark Stoodley, Vijay Sundaresan, Thomas Wong IBM Toronto Lab Compilation Technology 9/17/2019

2 Agenda Introduction Practical Dataflow Analysis
Program Transformation Overview Results and Summary 9/17/2019

3 Introduction Local Variable assignment is redundant if execution can follow a path where the assigned variable is dead Goal: remove such redundant assignments Transformation: move an assignment past the blocks to avoid redundant store 9/17/2019

4 Optimization Assignment sinking is a widely implemented optimization in static compiler PRE-based algorithm is commonly used to implement the optimization Expensive to be used in dynamic compiler In Testarossa JIT compiler, a practical method is devised to do assignment sinking This presentation contains material which has Patents Pending 9/17/2019

5 Example BB5 x = a BB6 BB9 BB7 BB10 BB11 BB8 z = x + y z = x * 2
y = x / 2 9/17/2019

6 Example BB5 x = a BB6 BB9 x = a BB7 BB10 BB11 BB8 x = a z = x + y
y = x / 2 9/17/2019

7 Motivation Can speed up the execution if an assignment is sunk from hot or scorching to cold block x = BB5 Scorching Edge (x not live) = x BB6 BB7 9/17/2019

8 Motivation Can speed up the execution if an assignment is sunk from hot or scorching to cold block x = BB5 Scorching Edge (x not live) x = = x BB6 BB7 9/17/2019

9 Motivation BB5 BB7 BB9 BB13 i0 = i …. i = i0 + 1 .. = i0 … if ()
goto BB5 … … (use of i) 9/17/2019

10 Motivation BB5 BB7 BB9 BB13 i0 = i …. i = i0 + 1 .. = i0 … if ()
goto BB5 i = i0 + 1 … i = i0 + 2 … (use of i) 9/17/2019

11 Practical Dataflow Analysis
Formulate the dataflow problem in terms of partial liveness Partial liveness analysis Partial liveness => redundant assignment Solution to partial liveness indicates which blocks have both live and dead paths Use the solution to perform the assignment sinking transformation 9/17/2019

12 Dataflow Variables Liveness: a variable is live at the block on some path Live-On-All-Path (LOAP): a variable is live at the block on all the paths which follow it Live-On-Not-All-Path (LONAP): a variable is only partially live at the block Contain both live and dead successor paths 9/17/2019

13 Dataflow Equations Liveness Any-path backward dataflow analysis
A variable is live at the block on some paths Any-path backward dataflow analysis GEN set: set of variables used before possibly being assigned in the block KILL set: set of variables assigned in the block Liveness_out(b) = 4 (Liveness_in(bi)) " bi ` b’s successors Liveness_in(b) = GEN(b) 4 (Liveness_out(b) – KILL(b)) 9/17/2019

14 Dataflow Equations LOAP All-path backward dataflow analysis
A variable is live at the block and on all the paths that follows it All-path backward dataflow analysis GEN and KILL sets: same as Liveness LOAP_out(b) = 3 (LOAP_in(bi)) " bi ` b’s successors LOAP_in(b) = GEN(b) 4 (LOAP_out(b) – KILL(b)) 9/17/2019

15 Dataflow Equations LONAP
A variable is only partially live at the block Non-iterative dataflow equations in terms of LOAP and Liveness LONAP_out(b) = Liveness_out(b) – LOAP_out(b) LONAP_in(b) = Liveness_in(b) – LOAP_in(b) 9/17/2019

16 LOAP Example BB5 x = a LOAP_out=0 LOAP_in=1 LOAP_in=0 BB6 BB9
z = x + y y = x / 2 z = x * 2 9/17/2019

17 LONAP Example BB5 x = a LOAP_out=0 LONAP_out=1 LOAP_in=1 LONAP_in=0
z = x + y y = x / 2 z = x * 2 9/17/2019

18 LONAP Example BB5 x = a LOAP_out=0 LONAP_out=1 LOAP_in=1 LONAP_in=0
y = x + 2 y = x / 2 z = x * 2 9/17/2019

19 Design Considerations
LONAP indicates where an assignment can be beneficially sunk in terms of partial liveness Live ranges of variables changed when the assignment is sunk Use profile information to determine how an assignment is profitably sunk 9/17/2019

20 Design Considerations (Cont’d)
GEN and KILL are still needed to indicate where an assignment can be legally sunk Sinking an assignment successfully can yield opportunity for earlier assignments to be sunk Sinking assignment along exception edges 9/17/2019

21 Program Transformation Overview
Determine Liveness, LOAP and LONAP Blocks are analyzed in postorder fashion to identify the potential movable assignments Perform store placement pass to sink the potential movable assignments 9/17/2019

22 Store Placement Algorithm
Assignment is sunk according to: LONAP: sink along path where it is beneficial GEN / KILL: sink along path where it is legal Sunk assignments are placed in the target block or in a synthetic block which jumps to the target Dataflow is updated along the path where the assignment is sunk allow earlier assignments to be sunk without additional pass 9/17/2019

23 Store Placement Example
BB5 y = x + 1 x = a BB6 BB9 BB11 BB7 BB8 BB10 z = x + y y = x / 2 z = x * 2 9/17/2019

24 Store Placement Example
KILL_cursor: maintain the kill symbols of the traversed assignments of the block BB5 y = x + 1 x = a KILL_cursor(x)=1 BB6 KILL(x)=0 KILL(x)=0 BB9 BB11 KILL(x)=0 KILL(x)=0 BB7 KILL(x)=0 BB8 BB10 KILL(x)=0 z = x + y y = x / 2 z = x * 2 9/17/2019

25 Store Placement Example
‘x’ is cleared in KILL_cursor ‘x’ is set in KILL for the placement blocks BB5 y = x + 1 x = a KILL_cursor(x)=0 BB6 KILL(x)=1 KILL(x)=0 BB9 x = a . BB11 KILL(x)=0 KILL(x)=0 BB7 KILL(x)=1 BB8 BB10 KILL(x)=0 x = a z = x + y y = x / 2 z = x * 2 9/17/2019

26 Store Placement Example
Earlier assignment to ‘y’ can now be sunk BB5 y = x + 1 x = a KILL_cursor(x)=0 BB6 KILL(x)=1 KILL(x)=0 BB9 x = a BB11 KILL(x)=0 KILL(x)=0 BB7 KILL(x)=1 BB8 BB10 KILL(x)=0 y = x + 1 x = a z = x + y y = x / 2 z = x * 2 9/17/2019

27 Results: Sinking Opportunities
Compile Time SPECjvm98 No. of Method Assignment Sunk Assignment Placed Compress 45 164 213 jess 91 336 463 db 52 218 289 javac 224 931 1173 mpegaudio 84 266 351 mtrt 60 207 333 jack 110 580 1032 Run on x86-32 Win, 3.0GHz, 1.5G RAM 9/17/2019

28 Results: Compile Time Overhead
SPECjvm98 Scorching Compile (ms) PRE Cost / Scorching (%) Partial Liveness Cost / Scorching (%) Partial Liveness Cost / Overall (%) compress 970 72 3.7 1.1 jess 2480 19 8.8 1.9 db 783 55 0.8 javac 500 20 2.4 0.0 mpegaudio 1230 60 6.0 1.3 mtrt 6853 45 41 1.6 jack 3436 35 1.8 0.3 Run on x86-32 Win, 3.0GHz, 1.5G RAM 9/17/2019

29 Results: x86-32 Performance
9/17/2019

30 Results: x86-64 Performance
9/17/2019

31 Summary Practical dataflow solution to do assignment sinking is presented which is used in Testarossa JIT Compiler Compile time overhead is negligible Performance improvement is found in the benchmarks Future work: need new tuning to boost up more performance 9/17/2019

32 Questions ? 9/17/2019

33 Thank You. 9/17/2019

34 Backup 9/17/2019

35 Tuning Example BB8 x = a z = x + y Last use of x here 9/17/2019

36 Tuning Example After applying CSE and DSE BB8 x = a z = a + y
Last use of x here 9/17/2019

37 Critical Edge Example x = = x 9/17/2019

38 Critical Edge Example x = x = = x 9/17/2019

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