Sound and Precise Analysis of Parallel Programs through Schedule Specialization Jingyue Wu, Yang...

Sound and Precise Analysis ofParallel Programs through

Schedule Specialization

Jingyue Wu, Yang Tang, Gang Hu, Heming Cui, Junfeng YangColumbia University

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Motivation

soundness (# of analyzed schedules / # of total schedules)

precision Total Schedules

AnalyzedSchedules

StaticAnalysis

DynamicAnalysis

AnalyzedSchedules

?

• Analyzing parallel programs is difficult.

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• Precision: Analyze the program over a small set of schedules. • Soundness: Enforce these schedules at runtime.

Schedule Specialization

soundness (# of analyzed schedules / # of total schedules)

precision Total Schedules

StaticAnalysis

DynamicAnalysis

AnalyzedSchedules

EnforcedSchedules

ScheduleSpecialization

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Enforcing Schedules Using Peregrine

• Deterministic multithreading– e.g. DMP (ASPLOS ’09), Kendo (ASPLOS ’09), CoreDet

(ASPLOS ’10), Tern (OSDI ’10), Peregrine (SOSP ’11), DTHREADS (SOSP ’11)

– Performance overhead• e.g. Kendo: 16%, Tern & Peregrine: 39.1%

• Peregrine– Record schedules, and reuse them on a wide range of

inputs.– Represent schedules explicitly.

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• Precision: Analyze the program over a small set of schedules. • Soundness: Enforce these schedules at runtime.

Schedule Specialization

soundness (# of analyzed schedules / # of total schedules)

precision

StaticAnalysis

DynamicAnalysis

AnalyzedSchedules

EnforcedSchedulesSchedule

Specialization

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Framework

• Extract control flow and data flow enforced by a set of schedules

Schedule

ScheduleSpecializationProgram

C/C++ programwith Pthread

Total order ofsynchronizations

SpecializedProgram

Extra def-usechains

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Outline

• Example• Control-Flow Specialization• Data-Flow Specialization• Results• Conclusion

Running Example

int results[p_max];int global_id = 0;

int main(int argc, char *argv[]) { int i; int p = atoi(argv[1]); for (i = 0; i < p; ++i) pthread_create(&child[i], 0, worker, 0); for (i = 0; i < p; ++i) pthread_join(child[i], 0); return 0;}

void *worker(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

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Thread 0 Thread 1 Thread 2

create

create

join

join

lock

unlocklock

unlock

Race-free?

Control-Flow Specializationint main(int argc, char *argv[]) { int i; int p = atoi(argv[1]); for (i = 0; i < p; ++i) pthread_create(&child[i], 0, worker, 0); for (i = 0; i < p; ++i) pthread_join(child[i], 0); return 0;}

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create

create

join

join

atoi

++i

create

return

i = 0

i < p

++i

join

i < p

i = 0

Control-Flow Specializationint main(int argc, char *argv[]) { int i; int p = atoi(argv[1]); for (i = 0; i < p; ++i) pthread_create(&child[i], 0, worker, 0); for (i = 0; i < p; ++i) pthread_join(child[i], 0); return 0;}

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create

create

join

join

atoi

++i

create

return

i = 0

i < p

++i

join

i < p

i = 0

atoi

create

i = 0

i < p

Control-Flow Specializationint main(int argc, char *argv[]) { int i; int p = atoi(argv[1]); for (i = 0; i < p; ++i) pthread_create(&child[i], 0, worker, 0); for (i = 0; i < p; ++i) pthread_join(child[i], 0); return 0;}

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create

create

join

join

atoi

++i

create

return

i = 0

i < p

++i

join

i < p

i = 0

create

atoi

i = 0

i < p

create

++i

create

i < p

Control-Flow Specializationint main(int argc, char *argv[]) { int i; int p = atoi(argv[1]); for (i = 0; i < p; ++i) pthread_create(&child[i], 0, worker, 0); for (i = 0; i < p; ++i) pthread_join(child[i], 0); return 0;}

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create

create

join

join

atoi

++i

create

return

i = 0

i < p

++i

join

i < p

i = 0

atoi

create

i = 0

i < p

++i

create

i < p

++i

i < p

join

i < p

i = 0

++i

join

i < p

++i

i < p

return

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Control-Flow Specialized Program

int main(int argc, char *argv[]) { int i; int p = atoi(argv[1]); i = 0; // i < p == true pthread_create(&child[i], 0, worker.clone1, 0); ++i; // i < p == true pthread_create(&child[i], 0, worker.clone2, 0); ++i; // i < p == false i = 0; // i < p == true pthread_join(child[i], 0); ++i; // i < p == true pthread_join(child[i], 0); ++i; // i < p == false return 0;}

atoi

create

i = 0

i < p

++i

create

i < p

++i

i < p

join

i < p

i = 0

++i

join

i < p

++i

i < p

return

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More Challenges onControl-Flow Specialization

• Ambiguity

call

Caller Callee

call

S1

• A schedule has too many synchronizations

ret

S2

Data-Flow Specialization

int global_id = 0;

void *worker.clone1(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

void *worker.clone2(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

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Thread 0 Thread 1 Thread 2

create

create

join

join

lock

unlock

lock

unlock

global_id = 0

my_id = global_idglobal_id++

my_id = global_idglobal_id++

Data-Flow Specialization

int global_id = 0;

void *worker.clone1(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

void *worker.clone2(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

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Thread 0 Thread 1 Thread 2

create

create

join

join

lock

unlock

lock

unlock

global_id = 0

my_id = global_idglobal_id++

my_id = global_idglobal_id++

Data-Flow Specialization

int global_id = 0;

void *worker.clone1(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

void *worker.clone2(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

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Thread 0 Thread 1 Thread 2

create

create

join

join

lock

unlock

lock

unlock

global_id = 0

my_id = 0global_id = 1

my_id = global_idglobal_id++

Data-Flow Specialization

int global_id = 0;

void *worker.clone1(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

void *worker.clone2(void *arg) { pthread_mutex_lock(&global_id_lock); int my_id = global_id++; pthread_mutex_unlock(&global_id_lock); results[my_id] = compute(my_id); return 0;}

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Thread 0 Thread 1 Thread 2

create

create

join

join

lock

unlock

lock

unlock

global_id = 0

my_id = 0global_id = 1

my_id = 1global_id = 2

Data-Flow Specialization

int global_id = 0;

void *worker.clone1(void *arg) { pthread_mutex_lock(&global_id_lock); global_id = 1; pthread_mutex_unlock(&global_id_lock); results[0] = compute(0); return 0;}

void *worker.clone2(void *arg) { pthread_mutex_lock(&global_id_lock); global_id = 2; pthread_mutex_unlock(&global_id_lock); results[1] = compute(1); return 0;}

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Thread 0 Thread 1 Thread 2

create

create

join

join

lock

unlock

lock

unlock

global_id = 0

my_id = 0global_id = 1

my_id = 1global_id = 2

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More Challenges onData-Flow Specialization

• Must/May alias analysis– global_id

• Reasoning about integers– results[0] = compute(0)– results[1] = compute(1)

• Many def-use chains

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Evaluation

• Applications– Static race detector– Alias analyzer– Path slicer

• Programs– PBZip2 1.1.5– aget 0.4.1– 8 programs in SPLASH2– 7 programs in PARSEC

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Program Original Specialized

aget 72 0

PBZip2 125 0

fft 96 0

blackscholes 3 0

swaptions 165 0

streamcluster 4 0

canneal 21 0

bodytrack 4 0

ferret 6 0

raytrace 215 0

cholesky 31 7

radix 53 14

water-spatial 2447 1799

lu-contig 18 18

barnes 370 369

water-nsquared 354 333

ocean 331 292

StaticRaceDetector

# of FalsePositives

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Program Original Specialized

aget 72 0

PBZip2 125 0

fft 96 0

blackscholes 3 0

swaptions 165 0

streamcluster 4 0

canneal 21 0

bodytrack 4 0

ferret 6 0

raytrace 215 0

cholesky 31 7

radix 53 14

water-spatial 2447 1799

lu-contig 18 18

barnes 370 369

water-nsquared 354 333

ocean 331 292

StaticRaceDetector

# of FalsePositives

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Program Original Specialized

aget 72 0

PBZip2 125 0

fft 96 0

blackscholes 3 0

swaptions 165 0

streamcluster 4 0

canneal 21 0

bodytrack 4 0

ferret 6 0

raytrace 215 0

cholesky 31 7

radix 53 14

water-spatial 2447 1799

lu-contig 18 18

barnes 370 369

water-nsquared 354 333

ocean 331 292

StaticRaceDetector

# of FalsePositives

25

Program Original Specialized

aget 72 0

PBZip2 125 0

fft 96 0

blackscholes 3 0

swaptions 165 0

streamcluster 4 0

canneal 21 0

bodytrack 4 0

ferret 6 0

raytrace 215 0

cholesky 31 7

radix 53 14

water-spatial 2447 1799

lu-contig 18 18

barnes 370 369

water-nsquared 354 333

ocean 331 292

StaticRaceDetector

# of FalsePositives

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Static Race Detector: Harmful Races Detected

• 4 in aget• 2 in radix• 1 in fft

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Precision of Schedule-AwareAlias Analysis

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Precision of Schedule-AwareAlias Analysis

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Precision of Schedule-AwareAlias Analysis

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Conclusion and Future Work

• Designed and implemented schedule specialization framework– Analyzes the program over a small set of schedules– Enforces these schedules at runtime

• Built and evaluated three applications– Easy to use– Precise

• Future work– More applications– Similar specialization ideas on sequential programs

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Related Work

• Program analysis for parallel programs– Chord (PLDI ’06), RADAR (PLDI ’08), FastTrack (PLDI ’09)

• Slicing– Horgon (PLDI ’90), Bouncer (SOSP ’07), Jhala (PLDI ’05), Weiser

(PhD thesis), Zhang (PLDI ’04)• Deterministic multithreading

– DMP (ASPLOS ’09), Kendo (ASPLOS ’09), CoreDet (ASPLOS ’10), Tern (OSDI ’10), Peregrine (SOSP ’11), DTHREADS (SOSP ’11)

• Program specialization– Consel (POPL ’93), Gluck (ISPL ’95), Jørgensen (POPL ’92),

Nirkhe (POPL ’92), Reps (PDSPE ’96)

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Backup Slides

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Specialization Time

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Handling Races

• We do not assume data-race freedom. • We could if our only goal is optimization.

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Input Coverage

• Use runtime verification for the inputs not covered

• A small set of schedules can cover a wide range of inputs

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