Transcript Prefetching for Mobile Computers Using Shape Graphs Kristian Kvilekval and Ambuj Singh University of California, Santa Barbara LCR'02 Kristian Kvilekval UCSB.

Prefetching for Mobile Computers
Using Shape Graphs
Kristian Kvilekval and Ambuj Singh
University of California, Santa Barbara
LCR'02
Kristian Kvilekval UCSB
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Prefetching for Mobile
Applications
•Application on Mobile Computer
•Access remote store objects
•Periodic interruption
Cache
•Object Oriented Databases
•Distributed Object system
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Our Approach
 Code-based prefetching
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Prefetch only those objects accessed by the code
Extract program access patterns
Provide runtime system with future accesses
 Advantages



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Complex pointer-based structures
Prefetches cold misses
Good accuracy
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Capturing Access Pattern
Statically
 Shape Analysis

Represents runtime data structures at compile
time as graphs
 Applications: extracts properties of programs
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Synchronization[Bogda99][Ruf00]
Parallelization[Corbera99]
Safety[Ghiya96][Nurit98][Wilhem00]
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Basic Shape Analysis
 Graph


Abstract locations (heap cells)
Edges labeled with with field names
 Abstract interpretation
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Extend graph through field references
Combine graphs when heap location is shared
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Example shape
class Connector{ Part a,b; }
class Part {
Connector left,right,up,down;
Material m
Supplier s;
…
int volume();
}
part
right
part
connector
material
weight=0;
while (part) {
weight+=(part.material.density
*part.volume());
part=part.right.b;
}
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Construction of Shape Graphs
x
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Construction of Shape Graphs
x.f = s;
F
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Construction of Shape Graphs
x.f = s;
t = x.f.g;
F
G
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Construction of Shape Graphs
x.f = s;
x.f.g = t;
N
F
?
x = x.n;
G
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Construction of Shape Graphs
N
x.f =
x.f.g
if (x
x =
s;
= t;
!= null)
x.n;
F
G
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Combining Shape Graphs
x = y;
N
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F
F
G
K
J
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Combining Shape Graphs
 Unify graphs recursively
N
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F
F
G
K
J
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Unification of Shape Graphs
 Unify graphs recursively
N
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N
F
F
G
K
J
F
G
J
K
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Shape Analysis Algorithm
  methods Interpret basic blocks


Create shapes for basic blocks
Run until fixed-point is reached
 Propagate in static callgraph
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Static Call Graphs
Static representation of calls
m3{
a.f = s;
o.m4(a)
}
Class C {
m4(F f) {
…
}
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main
m2
m3
m4
Unify(a,f)
f
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Call Graphs
 Propagate bottom up
 Merge polymorphic calls
m1
m2
m3
m4
B.m4
D1.m4
D2.m4
 Recursive Calls


Fixed point
Merge SCC[Ruf00]
m1
m2
m1
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Prefetching with shape graphs
 Compile Time
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Generate shapes for method references
Self, arguments, and global variables
 Label shape edges with earliest access

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Annotate programs to pass visible references and
method ID to runtime
 Runtime
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Interpret shape graph on the actual object graph
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Prefetching with Shape Graphs
N:5
a1
F:10
J:10
a2
G:5
a3
o1:0
a4
K:10
F
o2:10
K
N
o4:5
J
o5:15
N
o6:10
J
o3:20
a5
(o1,a1) » (o4,a1) » (o2,a2) » (o6,a1) » (o5,a4) » (o3,a5)
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Evaluation
 Java specjvm benchmarks
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Track all objects accesses
 Disconnects
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Cache
Poisson/Gaussian
Duration: 500
 Prefetching
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Interval: 2
Lookahead: 512
Cache: 2048
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jess
Expert System
db
Address DB
mtrt
ray tracer
OO7
OO database
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mtrt cold-misses
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OO7 all cold-misses
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OO7 Startup cold-misses
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Benchmarks
Benchmark
Initialized
INF:cold
PRE:cold
Time INF
Time PRE
jess
11196
1182
27
328K
310K
Db
528
51
1
11002
3982
mtrt
179527
2498
3
1803K
1222K
OO7
228535
107550
1
3133K
2547K
Infinite lookahead with infinite cache
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Effect of Varying Disconnect
Cost
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Effect of Varying Cache Size
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Prefetcher Overhead
benchmark
jess
objects
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mtrt
26462
2048
209630
cache
1024
4096
10240
20480
40960
Discards cache
34386 10941 6707
24132
21073
30748
Discards pre
73350 5335
48432
16496
13213
1243
Jess \ Lookahead
0
64
256
512
1024
2048
Runtime
401K
375K
358K
357K
346K
346K
Discards
0
10K
6K
7K
7K
8.4K
wait
0
79
82
83
83
83
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Future Extensions
 Accuracy and Overhead
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Dynamic runtime values (hashtable)
Find high-payoff points (callgraph,history)
 Balancing prefetching with
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cache, bandwidth, and power.
 Tuning prefetcher to link stability

And phase behavior of programs
 Extend shape analysis to work at runtime
 Apply to non-mobile systems.
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Similar Approaches
 Classfiles [Krintz98]

Earliest method invocation through callgraph and block analysis
 Slices for multithreaded processors [Collins01][Zilles01]
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Preexecute data operations ahead of program
 I/O extraction[Mitra00]
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Extract I/O related variables and execute in separate thread.
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Conclusions
 Code-based prefetching technique for
complex pointer-based structures
 Able to prefetch cold misses
 Good accuracy
[email protected]
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New Style Applications
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Mobile
Disconnections
Collaborative
Sharing
Serverless
Distribution
Dynamic
Network-topology
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Collaborative Mobile
Applications
 Calendar, Whiteboard, Bibliographer
 Cooperative Web cache
 Emergency services
 Games
 Construction/Filming/Concerts
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Prefetching for availability
 File Systems

Explicit or Structured
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Coda [Kistler92], Ficus/Rumor/Roam [Guy98]
Prediction (SEER[Keunning97])

Cluster based on file opens
 Databases
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Attributes [Phatak99]
Checkout [Holliday00]
Object Bases[Knafla99]
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Access patterns applied to object structure
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Mobile Model
Groups
Wireless
Portable
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