THE FRACTAL STRUCTURE OF DATA REFERENCE- P29 ppsx
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Index
Access density, 113, 120, 123, 125
Arrival rate, 35, 39
Back end I/O, 15
Back end, 12,15 Generation, 75
-
76
Benchmark, 35, 42
Binary tree, 37 Heavy
-
tailed, 1, 7, 85, 98
Burst, 6, 88
CA
-
ASTEX, 14
Cache Analysis Aid, 14
Cache visit, 13
Cache 107, 110
Front
-
end miss, 23
Garbage collection, 71
Generalized LRU,
67-68
Granularity, 11, 86, 91, 96
Henley, M., 5
Hierarchical reuse model, 1, 5, 7, 35, 47, 56, 78, 80,
Hierarchical storage management, 97, 99, 103
-
04,
87-88, 106
memory, 16, 22, 43-44, 51-52, 56, 59, 61-63,
Hi
n
t
s
,
53
66, 68 Hiperpool, 55
plain vanilla, 2 Hiperspace, 55
residency time,
9, 22, 26, 43-45, 47-48
storage control, 1
-
3, 8, 22, 25, 51-53, 55
-
56, 59
visit, 11
History dependent, 76, 81, 83
History independent, 76
Hit ratio, 2, 59
Hit, 2, 52
Homogeneous pattern of updates, 77, 80
Hyperbolic, 7
I/O interface, 51, 53
IMS, 22, 53, 89, 97, 110
Independent reference model, 3, 5, 69
Interarrival lime, 8–9, 78, 85, 87
Level 0 storage, 103
Level 1 storage, 103, 105, 112
Level 2 storage, 103
Linear model, 74, 77, 80,
83
Little’s law, 13, 16, 24, 79, 81
Little, J. D. C., 13
Log structured array, 71
Log-structured disk subsystem, 71
Calibration, 107
CICS, 18, 53, 89, 97, 110
Collection threshold, 76
Compression, 71, 103
-
104, 112
Constrained optimization, 104
-
105, 108
Contour plot, 110
Criterion of time
-
in
-
cache, 8, 14, 52
Cylinder image, 86
David
-
Johnson approximation, 38
DB2, 18, 53, 74, 89, 97, 110
Deferred write, 74
Deployable applications model, 114, 120, 123
-
124
Destage, 72, 74, 82
-
83
Dirty data, 82
Disk array, 71
DL/I, 22
Dormitory, 74 LRU, 2, 55, 61, 63
Driver, 35, 42 LRU
-
K, 68
Early demotion, 24, 55
ECKD, 2
Fractal, 11, 42
Free space collection, 71, 74, 77, 83
Front end, 12
-
13, 15, 87
Levy, Paul, 8
Mandelbrot, Benoit B., 7, 118
Memory hierarchy, 1, 5, 27
Memoryless, 1, 3, 5
Migration age, 105, 110
-
111
132
Migration, 103, 106
Miss ratio, 2,
16-17,
47, 66
Miss, 2 Skew, 122
Moves per write, 72, 80
MRU, 2
Multiple workload hierarchical reuse model, 33, 47,
Operational conventions, 82
OS/390 Stage,
2,
55
THE FRACTAL STRUCTURE OF DATA REFERENCE
Single
-
reference residency time, 8, 14, 36, 43,
52
-
53, 56, 63, 87
SMF, 46, 86, 96, 110
SMS Optimizer, 110
SMS, 97, 103
61 Solid state disks, 4
Stack distance, 42
Steady state, 86
Storage cost, 120
Storage intensity, 1 16, 118, 120
Synthetic application, 37
Tape robotics, 109
-
110, 112
Thiébaut, Dominique, 42
Tivoli Storage Manager, 103
Touch, 15, 88
Toy application, 35, 37
Track image, 2, 86
Transaction volume, 115, 117
Transient, 1, 61, 73, 80, 85
-
87, 89, 91, 99
TSO, 22, 97, 110
Usable capacity, 124
-
125
environment, 2, 9, 14, 23
-
25, 46, 103
workload measurements, 6, 18, 27, 89, 97, 110
Page frame, 11
Page, 2 Storage utilization, 76-77
Pareto, Vilfredo, 8
Partitioned memory, 63
Persistence metric, 87
-
88, 91
Persistent, 85
-
86, 89, 91, 96, 99, 101
Power law, 8, 17, 118
Primary storage, 97, 103,105, 112
Processor file buffer, 1, 9, 25, 33, 5
1,
53,
56,
59
Productivity, 104
Random walk, 37
Recall, 103, 106
Record, 2 Update
-
in
-
place, 7 1
Replacement criterion, 2
SAS, 110 VLF/LLA, 55
Secondary storage, 103 VM
Segment, 74
Self
-
similar, 7, 1 18
Sequential, 24, 68, 75 Window, 87, 89, 91
Service time, 116
Simulation, 39
-
40, 52
-
53
environment, 2, 9, 14, 24
workload measurements, 9, 18, 78
Sequential prestage, 24 VSAM, 22, 53
Working hypothesis, 43, 47, 50
Write promotions, 46
About the Author
Bruce McNutt is a senior scientist/engineer working in
the Storage Subsystems Division of International Business
Machines Corporation. He has specialized in disk storage
performance since joining IBM in 1983. Among the many
papers which he has presented to the annual conference
of the Computer Measurement Group, as an active par
-
ticipant for more than fifteen years, are two that received
CMG “best paper” awards. The present book brings to
-
gether two threads which have run through his work: the
hierarchical reuse model of data reference, first introduced in 1991 , and the
multiple
-
workload approach to cache planning, first introduced in 1987. Mr.
McNutt received his B.S. degree in mathematics from Stanford University, and
his master’s degree in electrical engineering and computer science from the
University of California at Berkeley.
