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The distributions W x and V x are standard queueing quantities and convey some performance information. Another performance measure, one that is less dependent on notions of stability and existence of moments, is the time until buffer over ow. We formulate the time to buffer over ow as the hitting time of a high level L: t L : inf ft ! 0 : X t ! Lg: W De ne M t ts 0 X s maxfX s : 0 s tg, and the reason for interest in the maximum content up to t is that as a process it is the inverse of the t process since t L inf fs > 0 : X s ! Lg inf fs > 0 : M s ! Lg : M 2 L ; where M 2 is the right continuous inverse of the monotone function M . If we understand the asymptotic behavior of M , then we will understand the asymptotic behavior of t . To understand the behavior of M we rst study the extremes of fX Sn g and then ll in the behavior between the discrete points fSn g. We study the maxima of the random walk generated by fxn g over cycles and then knit cycles together. Recall xn 1 1 r Xn 1 rYn 1 :



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14 Jul 2019 ... Tess4J ## Description: A Java JNA wrapper for Tesseract OCR API. Tess4J is released and distributed under the Apache License, v2.0.

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It gives instructions on how to build a java project to read an image and convert it into text using the tesseract OCR API.

Idle, 146, 149 Idle time interval, 208, 244 if-statement, 35, 49 ILP, see Integer linear program Index, 32 bound, 58 variable, 30 vector, 34 Insertion into gaps, 254 Insertion scheduling heuristic (ISH), 138, 149 Insertion technique, 145 149 de nition, 148 end technique, 148 Instance, 34, 53, 58, 59 Instruction ow, 7 stream, 7, 51 Integer linear program (ILP), 138, 182 Integer programming, 35 Intel Paragon, 11, 17, 195 Intel Pentium, 8 Interiteration, see Communication; Dependence Intermediate node, 20 Intermediate representation, 55 Intraiteration, see Communication; Dependence Intree, 153, 160 Involvement, 187, 229, 238, 249 characteristic, 232 236 direct, 233 function, 245 length, 233 type, 229, 232 Involvement scheduling, 238 250 algorithmic approaches, 257 causality condition, 242 edge scheduling, see Edge scheduling experimental results, 263 genetic algorithm, 261 heuristic, 229, 232, 257, 264 list scheduling, see List scheduling, involvement-contention node-edge order, 242 nonaligned, 243 NP-completeness, 248, 250 order overhead-involvement, 242 priority schemes, 260 two-phase, 261 Involvement-contention model, 238 homogeneous system, 240 task graph, 247





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xi ; n ! 0g is 0 : 7:2

Signals that an end of le or end of stream has been reached unexpectedly during input. Signals that an I/O exception of some sort has occurred. Signals that an I/O operation has been interrupted. Signals that the character encoding is not supported. Signals that a malformed UTF8 string has been read in a data input stream or by any class that implements the data input interface.

The tail behavior of the maximum in a (discrete) cycle is described next. See Asmussen [2] and Heath et al. [21]. Proposition 7.2.4. For the stable queueing process fX Sn g satisfying 1 Fon x x a L x ; a > 1; x 3 I;

the maximum over a cycle has a distribution tail asymptotic to the tail of the on distribution and, in particular, " P

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ISH, see Insertion scheduling heuristic Iteration, 32, 57, 64 number of, 58, 68 space, 55 Iteration dependence graph, 53 55 computer representation, 55 dimension, 53, 66 granularity, 55 irregular, 53 projection, 66 regular, 54 to ow graph, 66 Iteration-driven execution model, 57 Iterative block, 27 kernel, 64 Iterative data- ow program, 61 Iterative task graph (ITG), 61 KNAPSACK, 89 LAN (local area network), 37, 195 Latency, 12, 199 Leaf node, 20 Level bound, 97 Linear algebra, 27 Link, 13, 190, 196 directed, 193, 196 heterogeneous, 207 multidirectional, 196 Link set, 196 List scheduling, 108 119 clustering, see Clustering, list scheduling contention aware, 216, 218 220 complexity, 219 example, 218 dynamic priorities, 114 115 complexity, 114 115 example, 111 involvement-contention, 257, 261 complexity, 261 example, 259 with processor allocation, 262 node insertion, 148 149 complexity, 149 simple, 108 complexity, 112 with processor allocation, 119 involvement-contention, 262 Load balance, 180 Load balancing, 139 LogGP, 237

# X Sn > x $ P x1 > x E N $ P 1 r X1 > x E N a $ 1 r Fon x E N :

Note that this tail is lighter than the tail of W or V from the previous section. Interestingly, the off distribution in uences this expression only through the factor E N . From maxima over discrete cycles, it is relatively simple to derive tail behavior over a continuous time cycle: de ne C1 SN . Corollary 7.2.5. Assume the contents process fX t g is stable and 1 Fon x x a L x ; a > 1; x 3 I:

The distribution tail of the maximum of the contents process over one cycle is asymptotic to the tail of the on distribution; P C 1 W

LogP, 12, 189, 228, 235 237 generalized, 237 scheduling, 238 Lookahead technique, 137 Loop, 32 35, 49, 53, 56 body, 32, 54, 64 65 double, 34, 54 instance, 32 kernel, 32, 54, 65 double, 34 nest, 34, 54 stride, 35 transformation, 55 Makespan, 80 Mapping, 23, 51, 61, 75, 118, 120, 254 load minimization, 140 wrap, 140 Mapping heuristic (MH), 190 Massively parallel processors (MPP), 11 Matrix vector multiplication, 25, 27 MCP, see Modi ed critical path MD, see Mobility directed Meander, 183 Meiko CS-2, 231 Memory access policy, 9, 11 access time, 9 architecture, 9 11 centralized, 9 concurrent access, 11 12 distributed, 9 exclusive access, 12 hierarchy, 10 local, 10, 13 location, 9 organization, 9, 11 remote, 10 shared, 9 Memory architecture, 51 Memory bank, 20 Mergesort, 79, 115, 140 Mesh, 15 acyclic, 15 bisection width, 17 cyclic, 15 degree, 15 diameter, 15 dimension, 15 grid, 15 linear, 15 ring, 15 torus, 15 wrapped, 15

X s > x $ 1 r a Fon x E N :

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