Janus : exploiting parallelism via hindsight

John Field

Janus: exploiting parallelism via hindsight

Omer Tripp Roman Manevich

Mooly Sagiv

the PMD code analyzer

the PMD code analyzerpopular open-source code analyzer (~2,000 weekly

downloads)

the PMD code analyzerpopular open-source code analyzer (~2,000 weekly

downloads)

scans source files modularly =>

parallelization opportunity

the main loop of PMD (simplified)

the main loop of PMD

analyze files in parallel

but.. (shared as local)

hmm.. can’t we “localize” ctx?

the main loop of PMDnot so fast.. (happens sometimes, deep down the stack)

no cloning =>

reuse => @atomic ≈ @sequential

the main loop of PMDto summarize..

the main loop of PMDto summarize..available

parallelism

the main loop of PMDto summarize..available

parallelismmissed by write-set approach

Janus: sequence-based detection/* offlin

ctx.sourceCodeFilename = …;…String fname=ctx.sourceCodeFilename;…

Janus: sequence-based detectionT1

ctx.sourceCodeFilename = …;…ctx.setAttribute(s, …);…

ctx.sourceCodeFilename = …;…… = ctx.getAttribute(s);…

/* offline */

in paper:• more real-world examples• more coding patterns encouraging refined conflict detection

running example

Reverse-Delete MST

G’ = G(e1 … en) = SortEdgesByDecreasingWeight() for i=1 … n

G’.RemoveEdge(ei)if (!G’.HasPath(ei.u, ei.v))

G’.AddEdge(ei)return G’

running example

Reverse-Delete MST

ordered

running example

Reverse-Delete MST

running example

Reverse-Delete MST

identity if edge restored (available parallelism)

take I: blind parallelism

Reverse-Delete MST

parallel for // broken but fast

take II: write-set speculation

Reverse-Delete MST

G’ = G(e1 … en)= SortEdgesByDecreasingWeight() for i=1 … n

/* with boosting *

@atomic // exploit graph semantics: node ≈ location

take II: write-set speculation/* with b

oosting */

can we exploit the available

parallelism with this

approach?

the write-set approach in action

v1 v2uG:

RemoveEdge(u,v1) RemoveEdge(u,v2)T1 T2

v1 v2uG:

RemoveEdge(u,v1) RemoveEdge(u,v2)T1 T2

v1 v2uG:

RemoveEdge(u,v1)b = HasPath(u,v1)

v1 v2uG:

RemoveEdge(u,v1)b = HasPath(u,v1)test b

v1 v2uG:

RemoveEdge(u,v1)b = HasPath(u,v1)test bAddEdge(u,v1)

v1 v2uG:

take III: online commutativity checking

/* with boosting *

Reverse-Delete MST

@atomic // full commutativity checking

precise checking in action

v1 v2uG:

RemoveEdge(u,v1); HasPath(u,v1); AddEdge(u,v1)

v1 v2uG:

∙≡

but.. can we really afford this?

v1 v2uG:

expensive instrumentation

v1 v2uG:

expensive conflict detection+

v1 v2uG:

expensive conflict detection+

v1 v2uG:

expensive conflict detection+poor performance

take III: Janus/* with b

oosting */

Reverse-Delete MST

@atomic // accurate checking utilizing offline data!

the Janus approach

v1 v2uG:

the Janus approach

v1 v2uG:

sequence-based detection

the Janus approach

v1 v2uG:

sequence-based detection => accurate

the Janus approach

v1 v2uG:

candidate sequences learned ahead of production runs, in profiling

=> accurate

the Janus approach

v1 v2uG:

candidate sequences learned ahead of production runs, in profiling

commutativity testing done offline

=> accurate

the Janus approach

v1 v2uG:

candidate sequences gleaned ahead of production runs, in profiling

commutativity testing done offline

=> accurate=> cheap

the Janus flow

offline

the Janus flowfind candidate sequences via

profiling*ST runs*single

locations

offline

locations

offlinelow instrumentation

overhead

locations

test sequences for

commutativity

offline

locations

test sequences for

commutativity

cache (generalized version) of

commutative sequences

offline

locations

test sequences for

commutativity

offline

cheap conflict detection

locations

test sequences for

commutativity

offline

locations

test sequences for

commutativity

offline

online

the Janus flow

consult sequence cache

when attempting to

commit a transaction

find candidate sequences via

locations

test sequences for

commutativity

offline

online

the Janus flow

when attempting to

locations

test sequences for

commutativity

offline

online

miss perform write-set detection

the Janus flow

when attempting to

online

soundness

the Janus flow

when attempting to

locations

test sequences for

commutativity

offline

online

user input

the Janus spec: data

n2:v2 n3:v2

the Janus spec: data

node data

… …

neighbor node

… …

n2:v2 n3:v2

the Janus spec: operationsnode data

public void addnode(n) { nodes.add(n); }

the Janus spec: operations

node data

insert <n.d,n> into “nodes”

node data

the Janus flow

when attempting to

locations

test sequences for

commutativity

offline

online

sequence mining

v1 v2uG:

sequence mining

v1 v2uG:

G’ = G

sequence mining

v1 v2uG:

G’ = G(e1 … en) = SortEdgesByDecreasingWeight()

sequence mining

RemoveEdge(u,v1)T1

v1 v2uG:

sequence mining

v1 v2uG:

sequence mining

v1 v2uG:

RemoveEdge/T1; HasPath/T1

sequence mining

v1 v2uG:

sequence mining

v1 v2uG:

sequence mining

v1 v2uG:

RemoveEdge/T1; HasPath/T1; AddEdge/T1

sequence mining

RemoveEdge(u,v2)T1 T2

v1 v2uG:

sequence mining

RemoveEdge(u,v2)T1 T2

v1 v2uG:

RemoveEdge/T2

sequence mining

v1 v2uG:

RemoveEdge/T2

sequence mining

v1 v2uG:

sequence mining

v1 v2uG:

sequence mining

v1 v2uG:

sequence mining

v1 v2uG:

return G’

the Janus flow

when attempting to

locations

test sequences for

commutativity

offline

online

commutativity checking

RemoveEdge(u,v1

); HasPath(u,v1); AddEdge(u,v1)

RemoveEdge(u,v2

RemoveEdge(u,v1

RemoveEdge(x,y); HasPath(x,y); AddEdge(x,y)

RemoveEdge(x,z); HasPath(x,z); AddEdge(x,z)

ɸ0 = encode(G)ɸ1 = ɸ0 ˄ {x,y} ϵ “edges”…ɸk = ɸk-1 ˄ {x,y} ϵ “edges”…ɸk+1 = ɸk ˄ {x,y} ϵ “edges”…ɸm = ɸm-1 ˄ {x,y} ϵ “edges”

ψ0 = encode(G)ψ1 = ψ0 ˄ {x,z} ϵ “edges”…ψk = ψk-1 ˄ {x,z} ϵ “edges”…ψk+1 = ψk ˄ {x,y} ϵ “edges”…ψm = ψm-1 ˄ {x,y} ϵ “edges”

test: ¬(ѱ ≡ ɸ)

in paper:• encoding rules• “projection” : sound commutativity checking for sequences induced by individual memory locations

the Janus flow

when attempting to

locations

test sequences for

commutativity

offline

online

generalization RemoveEdge(x,y); HasPath(x,y);

AddEdge(x,y)S1= RemoveEdge(x,z); HasPath(x,z);

AddEdge(x,z)S2=

[S1 S2]G // “concrete” seq.s commute

AddEdge(x,z)S2=

S1(G) = S1∙S1(G) // idempotentS2(G) = S2∙S2(G) // idempotent

AddEdge(x,z)S2=

[S1+ S2

+]G // Kleene-cross generalization

AddEdge(x,z)S2=

[S1+ S2

+]G // Kleene-cross generalization

the Janus flow

when attempting to

locations

test sequences for

commutativity

offline

online

specialized spec

specialized commutativity specstate operation operation

any AddEdge(x,z)/ff AddEdge(x,y)/tt

any HasPath(z,w)/tt AddEdge(x,y)/ff

any[ RemoveEdge(x,z)/tt;

HasPath(x,z)/ff; AddEdge(x,z)/tt ]+

[ RemoveEdge(x,y)/tt; HasPath(x,y)/ff;

AddEdge(x,y)/tt ]+

tailored for given application

the Janus flow

when attempting to

locations

test sequences for

commutativity

offline

online

parallelization protocol

shared state [k]

shared state [k+1]

shared state [k+2]

privatized state [k]

privatized state [k’]

(a1 … an) (b∙ 1 … bm) Sk ≡ (b1 … bm) (a∙ 1 … an) Sk

shared state [k]

shared state [k+1]

shared state [k+2]

shared state [k]

shared state [k+1]

shared state [k+2]

shared state [k+3]

replay on shared

shared state [k]

shared state [k+1]

shared state [k+2]

shared state [k]

shared state [k+1]

shared state [k+2]

privatized state [k+2]

parallel reverse-delete MST

RemoveEdge(u,v1

)HasPath(u,v1)AddEdge(u,v1)

RemoveEdge(u,v1

)HasPath(u,v1)AddEdge(u,v1)RemoveEdge(u,v2

RemoveEdge(u,v1

RemoveEdge(u,v3

RemoveEdge(u,v1

RemoveEdge(u,v3

RemoveEdge(u,v1

RemoveEdge(u,v3

)HasPath(u,v3)AddEdge(u,v3) x.f =

y;||z = x.f;

RemoveEdge(u,v1

RemoveEdge(u,v3

RemoveEdge(u,v1

RemoveEdge(u,v3

state operation operation

AddEdge(x,y)/tt ]+

RemoveEdge(u,v1

RemoveEdge(u,v3

)HasPath(u,v3)AddEdge(u,v3)that’

s better..

benchmarksdescription name

utility for synchronizing pairs of directories JFileSync

greedy graph-coloring algorithm JGraphT-1 (coloring)

saturation-degree node-ordering algorithm for heuristic graph coloring

JGraphT-2 (ordering)

Java source code analyzer PMD

machine-learning library for data-mining tasks Weka

Seq 1 2 3 4 5 6 7 80

Fine-grained conflict detection

Coarse-grained conflict detection

Sequential

Seq 1 2 3 4 5 6 7 80

JGraphT-2

JFileSync

JGraphT-1 speedup

Fine-grained conflict detection

Coarse-grained conflict detection

1 2 3 4 5 6 7 80

JFileSync

1 2 3 4 5 6 7 80

JGraphT-2

1 2 3 4 5 6 7 80

JGraphT-1 retries

WekaPMDJGraphT-2 JFileSyncJGraphT-1

misses

W/ seq. abstraction W/O seq. abstraction

conclusions

profiling is useful for speculation• prevalent behaviors (dependencies) => effective

specialization• speculation = safety net

Janus enables practical accuracy boosting

• lifts commutativity checking to sequences of operations• runtime overhead comparable to write-set approach

Janus : exploiting parallelism via hindsight

Documents

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