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FIGURE 6.22 A schematic for a hybrid predictor. “Pred1” and “pred2” are configured as regular, standalone branch predictors (they might be a global-history and a local-history component, for example), but both components make a prediction and the selector then chooses one component prediction (via the multiplexor or “mux”) to use as its final prediction. The selector is a predictor too, but tracks component outcomes rather than branch direction outcomes. the PHT, the PHT is also 1 K entries. An unusual aspect of the PAg component is that it uses three-bit instead of two-bit saturating counters in order to achieve a stronger bias once the predictor has trained. The selector is also a 12-bit GAg predictor, but its PHT tracks which component has been more successful for each branch, rather than which direction the branch should take. Hybrid prediction has also been called “tournament,” “competitive,” and “combining” branch prediction. Other Issues in Predictor Organization The preceding sections have described the basic predictor organizations. Because prediction accuracy so strongly underpins processor performance, branch prediction remains an active area of research and a wealth of additional organizations have been proposed, primarily focusing on reducing mispredictions due to destructive aliasing. Interested readers should consult recent proceedings of the symposia and conferences in the list of works cited. It is worth noting, however, that researchers have also considered how to adapt branch prediction to wider-issue machines. Such a machine must fetch past multiple, possibly-taken branches in order to exploit the wider fetch width. Otherwise the processor becomes fetch-bottlenecked and its effective width is restricted by the average basic block size. Yeh, Marr, and Patt [29] describe a different branch address cache that learns segments of the controlflow graph and, in conjunction with a banked instruction cache, can fetch several blocks from noncontiguous cache lines in a single cycle. Conte et al. [28] describe a collapsing buffer that can also fetch past branches that are taken but whose target is in the same fetch block. Reinman, Austin, and Calder [46] decouple branch prediction from fetch, allowing the branch predictor to run ahead of fetch when possible, and they predict the length of fetch blocks so that not-taken branches do not unnecessarily limit fetching. The most aggressive proposal is the trace cache [30] of Rotenberg, Bennett, and Smith, which dynamically collapses noncontiguous fetch streams into contiguous traces that are stored in the trace cache and, which appears in the Intel Pentium® 4 [47] and the HAL Sparc64 V [48]. Sources of Mispredictions To better understand the behavior of branch predictors, it is helpful to examine some of the reasons a misprediction might occur. These reasons can be broken down into two broad categories: behavioral and structural. Behavioral mispredictions stem from the intrinsic behavior of a branch and are independent of the predictor’s organization. Any irregular or random behavior by a branch will inhibit its predictability. © 2002 by CRC Press LLC baddr selector (e.g.,GAg) pred1 (e.g., GAg) mux T/NT pred2 (e.g., PAg)
Structural mispredictions, on the other hand, stem from properties of the predictor’s hardware organization. The major structural sources of mispredictions are described below and come from [37]. Destructive PHT and BHT Conflicts All predictors that track state can suffer when unrelated branches map to the same predictor entry and interfere with each others’ state. In the predictor’s PHT or in a hybrid predictor’s selector PHT, destructive conflicts arise when branches map to the same 2-bit PHT counter and these branches go in opposite directions. In the BHT of a local-history predictor, destructive conflicts arise when branches map to the same history entry and hence the history of one branch displaces that of another branch. Note that constructive conflicts can also occur in all these structures when—for reasons of either luck or correlated behavior—the state of one branch causes a correct prediction by other branches. This means the expected gain from eliminating conflicts would eliminate both destructive and constructive conflicts, but the destructive behavior usually outweighs the constructive behavior. Training Time Because dynamic predictors work by recognizing patterns of branch behavior, they take time to train. The training time comes from two sources. First, the predictor must see enough branches to observe any patterns that exist. Second, the predictor must reach steady state. Consider the simple pattern TN,TN… in a 6-bit history. After this branch has been seen twice, the history will contain xxxxTN, where “x” signifies that these history bits contain a random value. Unless by sheer luck the bits in the “xxxx” portion happen to be TNTN, this pattern is a transient that will not be seen again. This branch must therefore be seen four more times before the history is fully initialized. In addition, for both types of training, a pattern must be seen often enough not only to initialize the branch history, but also to put the corresponding counters in the PHT into the proper state. In the TN,TN…example and assuming two-bit counters in the PHT, this means that the history TNTNTN must be seen twice in order to ensure that the two-bit counter has crossed the threshold. (The counter’s initial value might have been 00, but the correct prediction is T.) The larger the saturating counters, the longer this component of the training time. The predictor must train not only when a program first starts executing, but must also retrain after every context switch and also when the program’s behavior changes, either because it enters a new phase, or the nature of its input changes, etc. “Wrong” Type of History Mispredictions can also occur because the predictor does not track the most useful type of history—global or local—for the branch in question. This has been called wrong history, even though it does not imply that the actual history bits contain any invalid information. Unfortunately, most programs have some branches that do well with global history and some branches that do well with local history. A predictor that only tracks one or the other type of history therefore penalizes some branches in each program. Evers et al. showed this to be important in [34]. Skadron, Martonosi, and Clark [37] found wrong-history mispredictions are especially severe in global-history predictors, comprising 35–50% of the total misprediction rate. History Length Mispredictions might also arise even if the predictor tracks the correct type of history but it uses too short a history. For example, a history length of only two bits may not capture the full behavior of a pattern longer than 2 bits. Consider the pattern TNNN,TNNN.... A two-bit local history will learn that TN → N and this is always correct. But the problem arises for the pattern NN. The predictor will first learn NN → N, but on the fifth occurrence of the branch, this will cause a misprediction. On the other hand, there exist longer patterns for which short history is still sufficient. Consider two bits of history and the pattern TNNTT,TNNTT…. Although the overall pattern is longer than 2 bits, none of the distinct sub-patterns (TN, NT, and TT) are longer than two bits. Alternatively, the history can also be too long. The problem here is that the history may contain many bits that are entirely uncorrelated with the behavior of the branch to be predicted. This means that every © 2002 by CRC Press LLC
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© 2002 by CRC Press LLC
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© 2002 by CRC Press LLC Fernanda p
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Locating Your Topic Several avenues
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Krste Asanovic Massachusetts Instit
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7 8 9 Architectures for Low Power P
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SECTION VII Communications and Netw
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45 Testing of Synchronous Sequentia
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Hiroshi Iwai Tokyo Institute of Tec
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FIGURE 1.2 FIGURE 1.3 © 2002 by CR
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1.2 Downsizing below 0.1 © 2002 by
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FIGURE 1.9 Subthreshold leakage cur
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FIGURE 1.13 Epitaxial channel [9].
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gate length reduction was accelerat
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of the prediction. Until only sever
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FIGURE 1.22 Clarke number of elemen
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1.5 Source and Drain Figure 1.25 sh
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FIGURE 1.27 Retrograde profile. FIG
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TABLE 1.6 Trend of Interconnect by
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TABLE 1.9a Trend of DRAM Cell: Stac
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FIGURE 1.36 Trend of gate length. F
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References 1. D. Kahng and M. M. At
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40. B. H. Lee, R. Choi, L. Kang, S.
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outputs of the gate regardless of t
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FIGURE 2.4 circuit. This is the bas
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FIGURE 2.8 Two different realizatio
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FIGURE 2.12 Multifunction circuitry
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Dynamic Logic Circuits The basic id
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transistors in the pull-down networ
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In Fig. 2.21(d), the cross-coupled
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FIGURE 2.23 Different configuration
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In some literature, the authors lik
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Concluding Remarks The feature size
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FIGURE 2.30 Other pass-transistor c
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FIGURE 2.34 Dual-rail, pass-transis
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Shannon expansion, as shown below,
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FIGURE 2.41 Logic circuit for Out =
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FIGURE 2.45 Example decomposed BDD.
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FIGURE 2.50 Diffusion-area sharing
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FIGURE 2.54 Relationship between co
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29. Shiple, T. R., Hojati, R., Sang
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FIGURE 2.58 DTMOS devices: (a) stan
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the design into a BDD representatio
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FIGURE 2.63 Circuit diagram of 2-in
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FIGURE 2.67 Synthesis of 2-input AN
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pass-transistor logic, constrained
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16. Bryant, R., Graph-based algorit
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As shown in Fig. 2.79, the MOSFET d
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n + SiO 2 FIGURE 2.80 No reverse bo
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structures are a powerful solution
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SiO 2 Epitaxial Si Double Layered P
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PD-SOI Application to High-Performa
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LO FIGURE 2.91 History effects. sta
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weight, lower cost, a wireless inte
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TABLE 2.7 Performance of sub-1 V MT
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X X FIGURE 2.99 1 V A/D converter u
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When the communication range is 10
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13. Nakashima, S., et al., Thicknes
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FIGURE 3.1 Conventional ECL circuit
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FIGURE 3.4 FIGURE 3.5 IPULL-DOWN, f
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FIGURE 3.7 V REG voltage regulator
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FIGURE 3.10 Layout of inverter gate
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FIGURE 3.14 Power consumption versu
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I/O Pads, is 60 mW for the multiple
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FIGURE 3.21 Maximum data rate vs. V
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John C. McCallum National Universit
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enchmark took between 15.7 and 5115
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The improvements in line widths, ch
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performance. Extensive lists of SPE
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TABLE 4.6 Functions of Memory and S
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Memory Price ($/MB) FIGURE 4.3 Cost
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TABLE 4.8 Disk Drive Characteristic
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4.6 Summary The performance of comp
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53. Curnow, H. J., and Wichmann, B.
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Computer Systems and Architecture
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advances that have been made in dev
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Server Types Servers are optimized
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Total Cost of Ownership Another con
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edundant memory-bit steering, and s
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majority of the users. Hardware opt
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processor implementations. In later
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FIGURE 5.7 an operand. For larger c
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Example 2 This example contrasts th
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Unlike the Defoe, the IA-64 archite
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This 3-phase approach fails to expl
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6. Scott Rixner, William J. Dally,
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Shared-memory vector architectures
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The vector ISA usually fixes the ma
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FIGURE 5.12 A vector unit construct
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use of loops optimized for certain
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9. Espasa, R., Advanced Vector Arch
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thread management (including run-ti
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In the message passing model, inter
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multithreaded hardware, possibly by
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synchronization) and usually contai
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a common register space, it is impo
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FIGURE 5.16 When a load request is
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list a few helpful references to wh
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38. S. Wallace, B. Calder, and D. T
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Of course, SIMD machines have limit
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computation, it will decrease execu
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FIGURE 5.19 An 8 × 8 baseline netw
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Page 214 and 215: FIGURE 5.25 Shared memory. Shared m
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Page 218 and 219: In general, if the necessary transl
Page 220 and 221: Mark Smotherman Clemson University
Page 222 and 223: Studies of Instruction-Level Parall
Page 224 and 225: Modern Designs Most high-performanc
Page 226 and 227: The principle of register renaming
Page 228 and 229: FIGURE 6.2 issued into the RS, (ii)
Page 230 and 231: Issue Dispatch FIGURE 6.4 The proce
Page 232 and 233: FIGURE 6.6 Scope of register renami
Page 234 and 235: FIGURE 6.9 State transition diagram
Page 236 and 237: Thus, the maximal number of instruc
Page 238 and 239: In addition, if rename buffers are
Page 240 and 241: it, whose role will be explained su
Page 242 and 243: As Fig. 6.13 shows, the latest proc
Page 244 and 245: for recovery. Both processors incor
Page 246 and 247: FIGURE C. The principle of direct i
Page 248 and 249: 13. White, S. and Reysa, J., PowerP
Page 250 and 251: FIGURE 6.14 A branch flowing throug
Page 252 and 253: is that mispredictions limit the pr
Page 254 and 255: fetch engine to identify which inst
Page 256 and 257: FIGURE 6.17 A schematic for a bimod
Page 258 and 259: FIGURE 6.20 A schematic for a GAg g
Page 262 and 263: time this branch is seen, those bit
Page 264 and 265: FIGURE 6.23 Branch prediction accur
Page 266 and 267: 11. Price, C., MIPS IV Instruction
Page 268 and 269: transporting digital bits, whereas
Page 270 and 271: FIGURE 6.25 The system architecture
Page 272 and 273: Finally, because the main task of n
Page 274 and 275: Pradip Bose IBM T. J. Watson Resear
Page 276 and 277: frequency © 2002 by CRC Press LLC
Page 278 and 279: The “mips” metric for performan
Page 280 and 281: Hence, in this paper, we do not dwe
Page 282 and 283: FIGURE 7.4 Parallel SIMD architectu
Page 284 and 285: dynamic prediction of such idle mod
Page 286 and 287: FIGURE 7.7 High-level block-diagram
Page 288 and 289: (measured as a performance over pow
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Page 292 and 293: 8. Larson, A. G., “Cost-effective
Page 294 and 295: Jozo J. Dujmović San Francisco Sta
Page 296 and 297: x FIGURE 8.1 Movement of the disk I
Page 298 and 299: The critical distance x ∗ is Ther
Page 300 and 301: Hence, the average seek time for th
Page 302 and 303: FIGURE 8.4 Four-parameter exponenti
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Page 306 and 307: TABLE 8.1 Classification of Eight B
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Response Time [seconds] 290 270 250
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FIGURE 8.14 Prediction errors e(p)
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8.2 Performance Evaluation: Techniq
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is generally the most important mea
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tool to profile programs on the Alp
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driven simulation has two major pro
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A variety of profiling tools exist
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SPLASH, the SPLASH suite was create
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different types and complexity eith
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Table 8.8 provides sources for the
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37. MediaBench benchmarks, http://w
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(a) Instruction Cache (b) Trace Cac
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PE 0 Local Register File local bypa
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The large trace processor instructi
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11. S. Melvin, M. Shebanow, and Y.
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complement numbers. Sign magnitude
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where ak, bk, and ck are the inputs
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k + 1, etc. Extending to a third st
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a 12:15 b 12:15 4-Bit RCA s 12:15 F
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FIGURE 9.8 Two’s complement subtr
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FIGURE 9.10 Unsigned 6 by 6 array m
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Digit Recurrent Division The most c
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FIGURE 9.14 Nonrestoring division.
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The Newton-Raphson division algorit
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FIGURE 9.18 Floating-point addition
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9.2 Fast Adders and Multipliers Gen
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FIGURE 9.20 Half-adder circuit. is
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gi pi FIGURE 9.22(b) Carry skip cir
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Assuming that a single level of the
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Array-Type Multiplier The simplest
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p1i,j p2i,j p3i,j p4i,j FIGURE 9.27
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The partial product PP j is to be c
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The sum SGN of the whole extended b
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FIGURE 9.31 54 × 54-bit parallel m
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6. Svensson, C. and Tjarnstrom, R.,
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Design Techniques III 10 Timing and
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FIGURE 10.1 Typical chip interface.
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Loop Components PLLs and DLLs share
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delay is some fraction of the input
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esults from the voltage across the
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© 2002 by CRC Press LLC TABLE 10.2
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db(H( ω)) FIGURE 10.6 PLL closed-l
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ω )/G O) db(T(ω ph(T( )/π) FIGUR
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Phase Margin (deg) FIGURE 10.10 PLL
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FIGURE 10.11 Measured PLL jitter hi
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FIGURE 10.13 DLL output jitter sens
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FIGURE 10.18 PLL output jitter sens
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Active supply filters employ amplif
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FIGURE 10.19 Single-ended delay ele
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Frequency (GHz) FIGURE 10.23 Freque
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FIGURE 10.25 Push-pull charge pump.
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Circuit Summary In general, all DLL
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5. T. Lee, et al., “A 2.5V CMOS D
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introduced in [3], is used to repre
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FIGURE 10.31 Setup and hold time ti
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FIGURE 10.34 Max-timing diagrams fo
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FIGURE 10.37 Time borrowing for sin
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FIGURE 10.39 Max-timing for single-
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Min-Timing In contrast to max-timin
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FIGURE 10.46 Min-timing diagrams fo
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FIGURE 10.49 Edge-triggered, flip-f
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FIGURE 10.51 FIGURE 10.52 Max-timin
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FIGURE 10.53 Transparent-high latch
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FIGURE 10.57 Complementary TSPC tra
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FIGURE 10.61 A positive, edge-trigg
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FIGURE 10.66 Pulsed latches. FIGURE
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assigned, based on the subcircuit t
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FIGURE 10.71 Scan chain for dual-ph
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and SEB, which are complementary, c
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when used as a flip-flop, the NAND3
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FIGURE 10.75 Integrated memory for
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Memory Cell Bit# Bit FIGURE 10.78 A
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FIGURE 10.80 Modeling process varia
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FIGURE 10.83 A column circuit. FIGU
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advantage of this circuit, compared
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K. Wayne Current University of Cali
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11.2 Nonvolatile Multiple-Valued Me
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Multiple-Valued EEPROM and Flash Me
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direct properly scaled and logicall
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Current comparators are a critical
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FIGURE 11.4 Current-mode CMOS quate
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FIGURE 11.6 Current-mode CMOS quate
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observed with these circuits are ab
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FIGURE 11.11 Current-mode CMOS quat
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FIGURE 11.12 Current-mode CMOS latc
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FIGURE 11.14 Current-mode CMOS anal
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esults confirm the DC transfer func
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19. T. T. Dao, “Threshold I2L and
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FIGURE 12.1 Device technologies use
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selected depending on the number of
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Architecture of Newer Generation FP
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FIGURE 12.6 An example of a simple
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tools, the + 1 operation is a speci
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download the programming data to th
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FIGURE 13.1 High-performance microp
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FIGURE 13.4 TABLE 13.1 combinationa
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accurate wire modelling while limit
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FIGURE 13.6 Dual-rail, multiple-out
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FIGURE 13.10 Effect of output inver
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FIGURE 13.11 Unfooted dynamic 4:1 m
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(4) the limit of designers to manag
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© 2002 by CRC Press LLC IV Design
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FIGURE 14.1 FIGURE 14.2 newer semic
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The cost impact of power consumptio
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In any case, the move toward “Gre
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This static current is obviously un
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14.2 Power Estimation As we saw in
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lock as a function of various param
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FIGURE 14.8 Sleep transistors to co
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FIGURE 14.12 Data enabling. In addi
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Power Reduction through CAD Tools P
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AMPS AMPS is a circuit power optimi
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Masayuki Miyazaki Hitachi, Ltd. 15.
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15.3 Supply Voltage Management Supp
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FIGURE 15.4 MT-CMOS balloon circuit
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FIGURE 15.9 EVT-CMOS circuit design
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FIGURE 15.12 VT-CMOS block diagram
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FIGURE 15.15 SA-V t CMOS scheme wit
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FIGURE 15.17 Floating-point datapat
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Vivek De Intel Corporation Ali Kesh
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FIGURE 16.3 n-channel ID vs. VG sho
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Gate-Induced Drain Leakage (I 4) GI
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FIGURE 16.7 Two-nMOS stack in a two
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FIGURE 16.11 Four-input NAND NMOS s
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FIGURE 16.12 Distribution of standb
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Die count FIGURE 16.16 (a) Adaptive
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due to adaptive body bias worsens w
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Thomas D. Burd University of Califo
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the parameter to be maximized since
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17.3 Dynamically Varying Voltage If
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The voltage converter required for
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FIGURE 17.7 DVS improvement for UI
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FIGURE 17.10 Measured throughput vs
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FIGURE 17.12 Sources of noise margi
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FIGURE 17.15 Ring oscillator adapti
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FIGURE 17.17 Sense-amp delay variat
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Christian Piguet CSEM: Centre Suiss
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Some Basic Rules There are some bas
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TABLE 18.2 Looped 8-bit Multiply Pr
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FIGURE 18.4 new architecture paradi
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FIGURE 18.6 FIGURE 18.7 the second
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FIGURE 18.9 FIGURE 18.10 With latch
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18.6 Low-Power Memories As memories
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connected to the main bitline (only
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is today only about a factor of 2 d
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Katsunori Seno SONY Corporation 19.
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FIGURE 19.2 FIGURE 19.3 This is a c
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FIGURE 19.6 FIGURE 19.7 FPGA sacrif
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FIGURE 19.9 RAWn precharge FIGURE 1
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a fixed given standard. References
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Hendrawan Soeleman Purdue Universit
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for a short period of time when bot
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Total Average Power Putting togethe
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Signal Probability Calculation In c
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Example Given y = x 1 + x 2. Find P
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A B F FIGURE 20.7 Unfactorized and
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etween successive transitions is a
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FIGURE 20.9 A logic gate and its co
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Results Using Probabilistic Techniq
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FIGURE 20.12 Probabilistic and stat
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14. VLSI Microprocessors: A Guide t
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0 V to a voltage V in time T throug
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a small fraction of circuit nodes t
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FIGURE 21.6 (a) E-R latch, (b) timi
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FIGURE 21.8 Potential E-R latch for
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The only difference between the two
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FIGURE 21.14 (a) Clock-powered stat
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FIGURE 21.17 The three drivers used
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FIGURE 21.20 Energy-delay product (
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FIGURE 21.22 AC-1 clock-driver sche
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clock-powered nodes accounted for 8
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Two generations of clock-powered mi
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29. Athas, W. C., Tzartzanis, N., M
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Wayne Wolf Princeton University 22.
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so a CPU could be built in reconfig
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optimized processes. Although embed
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FIGURE 22.4 they are most useful wh
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• How should processes be allocat
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25 memory system activity. If the c
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Jonathan W. Valvano University of T
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FIGURE 23.2 6808, I/O ports A and B
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personnel so that they are proficie
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BDM can provide the ability to obse
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minor modifications to the finite s
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Many components are included in a d
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will saturate resulting in a bang-b
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Two approaches are used to synchron
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Fred J. Taylor University of Florid
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The output of a linear system havin
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FIGURE 24.2 Effects of windowing an
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frequency range ±f Nyquist = ±f s
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performance, complexity, and precis
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overflows of intermediate sums. Tha
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24.7 Applications “DSP” has bec
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DSP (Digital Signal Processor) or D
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PC as a Terminal (Modem) The PC is
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characteristics: • Fixed pictures
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HDTV (and Digital Television) If th
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Modem Banks This is the first of th
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25.7 Automotive, Industrial Althoug
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36. MITEL Semiconductor: www.semico
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26.2 Digital Filters The theory of
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|H | 1 FIGURE 26.1 Frequency select
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TABLE 26.1 Filter Design Comparison
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frequency response involves some al
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Impulse Response 0.2 0.15 0.1 0.05
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This constrained magnitude problem
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FIGURE 26.8 Block diagram of the ge
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11. Ikehara, M., Tanaka, H., and Ku
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Adam Dabrowski Poznan University To
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−12 2 The reference in this case
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FIGURE 27.1 Two-band filter bank: (
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FIGURE 27.5 Critical bandwidth and
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FIGURE 27.7 Threshold of audibility
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FIGURE 27.10 Critical band index in
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FIGURE 27.13 Simplified model of th
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All described masking effects are e
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where From Eqs. (27.32) and (27.33)
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eal-time. Although floating-point p
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FIGURE 27.19 Overlapped, power comp
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FIGURE 27.21 Symmetrical FIR filter
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In the MPEG-1 encoder an efficient
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These first two approaches can be m
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FIGURE 27.27 ADPCM: (a) encoder, (b
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FIGURE 27.30 General scheme of the
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A new standard MPEG-7, named the mu
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FIGURE 27.32 AC-3 encoder. FIGURE 2
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29. Marven, C. and Ewers, G., A sim
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FIGURE 28.1 FIGURE 28.2 of the huma
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FIGURE 28.5 image of reasonable qua
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Consider the case of a simple 2-D
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FIGURE 28.8 A sampled spatiotempora
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oth high spatial frequency componen
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If it were separable (that is, H(ξ
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The first hypothesis (the less plau
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FIGURE 28.17 The real (top) and ima
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FIGURE 28.18 The resolution of a ti
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FIGURE 28.20 Motion estimation by b
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where the superscripts n and n + 1
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must be found via a finite set of o
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The methods in this subsection are
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FIGURE 28.28 The split phase. Using
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35. Y.-T. Wu, T. Kanade, J. Cohn, a
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29.2 Power Dissipation in Digital C
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additional power benefits. Efficien
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Power savings are higher than simpl
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A priori knowledge of data stream d
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FIGURE 29.7 DCT Chip [my DCT] avera
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19. S. Uramoto et al. A 100 MHz 2-D
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Anna Hać University of Hawaii 30.1
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Using TCP/IP also makes the network
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this is for one mobile host which i
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TDMA Time-division multiple access
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path delay. The two measures of the
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are under the control of the system
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the bandwidth reserved in the targe
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Chik-Kong Ken Yang University of Ca
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FIGURE 31.3 attenuation (dB) -3.0 -
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FIGURE 31.5 to handle large voltage
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p_o V bias FIGURE 31.8 High-impedan
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out[n] a0 FIGURE 31.11 Transmitter
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FIGURE 31.15 Receiver design using
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digitally by first feeding the inpu
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FIGURE 31.19 90 o locking using XOR
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Power of these links is becoming an
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46. Takahashi, T. et al., “A CMOS
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Many computer programs exhibit some
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32.3 Related Memory Models, Hierarc
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32.6 External Sorting and Related P
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uns, each striped across the disks.
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Matrix transposition is the special
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of satellite images is over one ter
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TABLE 32.3 Best Known I/O Bounds fo
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e accessed directly in a single I/O
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implementations of priority queues
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By the reduction in [52], a data st
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set of experiments on various text
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3. A. Acharya, M. Uysal, and J. Sal
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44. J. L. Bentley and J. B. Saxe. D
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85. P. Ferragina and F. Luccio. Dyn
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128. V. Kumar and E. Schwabe. Impro
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173. H. Samet. The Design and Analy
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Peter J. Varman Rice University 33.
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need for fast transfers, up to 1 Gb
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In contrast to prefetching that mas
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The ERF algorithm was analyzed in [
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increment lowestPriorityOnDisk(disk
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External or out-of-core algorithms
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33. M. Kallahalla and P. J. Varman.
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advanced, reaching the point where
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FIGURE 34.3 FIGURE 34.4 defines the
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FIGURE 34.5 Trellis representation
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FIGURE 34.7 Data and servo sectors.
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References 1. S. H. Charrap, P. L.
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High-frequency noise is then remove
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The various components of (34.3) ar
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sequences are more complex, and occ
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ange of 10 −12 -10 −15 . Anothe
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strategies are reviewed, which have
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FIGURE 34.13 Magnitude response for
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taps as an approximation of the Typ
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FIGURE 34.18 CTF BER performance de
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TABLE 34.1 Examples of Equalizers I
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(i) Symbol rate VCO based timing re
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Symbol Rate Timing Recovery Schemes
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where B = B 1 + B 2 + 1 is the size
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in � out � d(k) FIGURE 34.26 Ti
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�(k) z -L FIGURE 34.27 Linearized
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10 −4 and 10 −2 . The steady-st
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16. J. Sonntag, et al., “A high s
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y a special sequence known as the a
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FIGURE 34.36 An example of two Gray
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track n track n +1 FIGURE 34.38 The
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FIGURE 34.40 The phase format. Posi
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increase linear density while mitig
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FIGURE 34.43 Two equivalent constra
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FIGURE 34.44 Possible pairs of sequ
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Distance δ min,C can be bounded as
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FIGURE 34.45 Standard concatenation
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30. E. Soljanin, “On-track and of
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The next block is PRE. What is PR?
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In the above example, we see that s
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FIGURE 34.52 Feedback detector. Cat
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FIGURE 34.54 Decision feedback equa
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esponse (this is also valid for dif
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its use, while the computational, o
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FIGURE 34.58 Viterbi algorithm dete
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Noise-Predictive Maximum Likelihood
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The error event likelihoods are cal
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Metric-First Algorithms Metric-firs
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termination at the same time. Howev
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13. J. Hagenauer, “Applications o
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Given a code C of length n and dime
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Notice that, although a code may ha
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Not many perfect codes exist. In th
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Theorem 1 (Shannon) For any � > 0
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If we write the codewords as polyno
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Let © 2002 by CRC Press LLC 1 1 K
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which, in polynomial form, is Let E
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m Σl=0 because a l = (a m+1 − 1)
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Evaluating the syndromes, we obtain
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FIGURE 34.63 Interleaving m times o
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Operating System © 2002 by CRC Pre
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systems, the most notable example b
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35.3 Components of Distributed Oper
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Message-passing IPC shares many cha
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process at any arbitrary stage in i
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Few attempts were made in the past
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alternate years with SOSP), and the
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© 2002 by CRC Press LLC 42 Mobile
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FIGURE 36.1 were introduced; howeve
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FPGAs by providing on-chip memory f
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FIGURE 36.3 There is a considerable
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FIGURE 36.4 The general form of the
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FIGURE 36.6 If a VPB can cover all
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John Morris University of Western A
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FIGURE 37.1 Simplified block diagra
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inverters, and the programmable mul
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Programmable Active Memories (PAM)
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measured in megabits, not megabytes
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from modern FPGAs, e.g., Altera’s
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Regularity A processing pipeline wi
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Other Languages Other routes from h
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29. Bergmann, N.W., and Dawood, A.,
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FIGURE 37.8 Basic architectures for
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Selected Applications Several class
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Development Systems Developing appl
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implementation. Reconfigurable or r
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The designer starts the generation
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lock but allows multiple instructio
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data-types that are mapped to TIE r
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Conclusions Configurable and extens
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FIGURE 38.1 Average vehicle speed.
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AHS means advanced cruise-assist hi
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TABLE 38.3 navigation systems VICS
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FIGURE 38.9 FIGURE 38.10 a map data
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FIGURE 38.13 The four basic functio
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Support of Safe Driving System The
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System evaluation, the fourth issue
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FIGURE 38.18 Summarizing the three
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uilder tools serving to build MMI o
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FIGURE 38.23 FIGURE 38.24 automaker
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FIGURE 38.26 FIGURE 38.27 The first
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FIGURE 38.30 FIGURE 38.31 a kind of
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To Probe Further In this field, the
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FIGURE 39.1 of more versatile media
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1 • 3DNow! 1 [11,12] from AMD,
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FIGURE 39.6 In the packed add instr
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If saturation arithmetic is used in
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TABLE 39.1 Examples of Operations T
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FIGURE 39.10 PAVG R c, R a, R b: Pa
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FIGURE 39.13 Packed compare instruc
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FIGURE 39.17 Packed multiply high i
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FIGURE 39.20 Packed multiply left i
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FIGURE 39.23 In the packed multiply
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TABLE 39.4 Packed Integer Multiplic
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Subword Permutation Instructions In
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is n log 2(n). Table 39.6 shows how
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FIGURE 39.33 Mix left instruction.
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TABLE 39.7 Subword Permutation Inst
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TABLE 39.9 IA-64 uses FPMA and FPMS
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The two-bit result field is written
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source register. These three FP mix
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13. Motorola, “AltiVec technology
Page 1118 and 1119:
FIGURE 39.48 ManArray 1 × 2 core e
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FIGURE 39.50 Hypercube interconnect
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FIGURE 39.53 Host DSP software laye
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Benchmark Data Type Performance 256
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FIGURE 39.56 Simplified schematic o
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Gaming applications often require a
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system, and the application program
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FIGURE 39.60 FIGURE 39.61 FIGURE 39
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FIGURE 39.64 shifting place limits
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FIGURE 39.66 pitch Address Looping
Page 1138 and 1139:
FIGURE 39.69 gain of the filter. It
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as a core to integrate onto the sam
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7. Rossum, D., Constraint based aud
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FIGURE 39.74 Procedure for simulate
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The fitness value of an individual
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FIGURE 39.77 The tabu list can be v
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Intermediate-term memory component
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FIGURE 39.81 Selection. FIGURE 39.8
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Work on parallelization of the tabu
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Acknowledgment The authors acknowle
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47. L. K. Grover. A new Simulated A
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93. E. M. Rudnick, J. H. Patel, G.
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138. Youn-Long Lin, Yu-Chin Hsu, an
Page 1164 and 1165:
This architecture allowed for large
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FIGURE 40.3 40.3 Application Server
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FIGURE 40.5 applications. CORBA cur
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FIGURE 40.8 The application server
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FIGURE 40.10 The proposed architect
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cost at the front end. The ideal ap
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FIGURE 40.12 Client-server and netw
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Yoshiaki Hagiwara Sony Corporation
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FIGURE 41.2 This corresponds to the
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FIGURE 41.5 Buried channel CCD stru
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FIGURE 41.8 Applications of CCD and
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sensor (1100 K pixel) Microphone ×
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�� FIGURE 41.14 Form com
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FIGURE 41.16 Stack technology. Link
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1st EmDRAM Product FIGURE 41.19 Emb
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FIGURE 41.23 Em-DRAM process techno
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John F. Alexander University of Nor
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Several reasons exist for mentionin
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sort of local area network. Support
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Technological hurdles must be overc
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FIGURE 42.1 Block diagram of (a) ge
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FIGURE 42.3 Alternative FIR filter
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FIGURE 42.5 Polyphase filter struct
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3. E. Dahlman, Bjorn Gudmundson, M.
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TABLE 42.1 Categorizing Reusable Co
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FIGURE 42.11 Internet growth. FIGUR
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FIGURE 42.13 Software for VoIP SoC.
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FIGURE 42.17 Bandwidth trends. FIGU
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The interconnections between the va
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FIGURE 42.21 A typical communicatio
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carry information over longer dista
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however, it is not uncommon that so
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node, to which the user is connecte
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its information. Intuitively, this
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This issue is referred to as latenc
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Evolution of Standard Image/Video C
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FIGURE 42.26 Sequence of zigzag-cod
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FIGURE 42.29 150th Frame of origina
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FIGURE 42.31 Data partitioning for
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for transmitting a predictively cod
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42.6 Pen-Based User Interfaces—An
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FIGURE 42.35 The handwriting recogn
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• No toggling between edit/contro
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FIGURE 42.39 Boxplots of time to en
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0 … 9 ( ) -
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is using the SMIL generic media ref
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FIGURE 42.47 Example of pen-and-pap
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slots specifying pieces of informat
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most stringent demands for low-powe
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FIGURE 42.51 MIPS requirement of se
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FIGURE 42.54 von Neumann architectu
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FIGURE 42.57 Dual Mac architecture
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FIGURE 42.59 Two data path variatio
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FIGURE 42.60 Basic pipeline archite
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References 1. Bahl L., Cocke J., Je
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Random Oracle Model One direction o
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at the end of its usefulness. A new
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function and verification function
Page 1280 and 1281:
underlies the Diffie-Hellman key ag
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31. Dolev, D., Dwork, C., and Naor,
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R. Chandramouli Synopsys Inc. 44.1
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many deficiencies in the design may
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impact the performance and test ove
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FIGURE 44.4 FIGURE 44.5 It becomes
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SoC methodologies require synchroni
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This method, however, lacks the app
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FIGURE 45.2 Input formats of MILEF
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FIGURE 45.3 FIGURE 45.4 Robustness
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FIGURE 45.5 In Fig. 45.5 a simple e
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difficult to identify for overcurre
Page 1304 and 1305:
General Approach in Comparison with
Page 1306 and 1307:
FIGURE 45.10 phase—the propagatio
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shorter test sequence could possibl
Page 1310 and 1311:
Looking at results of Table 45.6, i
Page 1312 and 1313:
45.4 Summary Automatic test pattern
Page 1314 and 1315:
41. F. Brglez, H. Fujiwara: A neutr
Page 1316 and 1317:
FIGURE 46.1 Rule of ten in testing
Page 1318 and 1319:
FIGURE 46.5 FIGURE 46.6 of the DUT.
Page 1320 and 1321:
FIGURE 46.7 generate tests for ever
Page 1322 and 1323:
FIGURE 46.9 FIGURE 46.10 behavioral
Page 1324 and 1325:
Z. Stamenković University of N. St
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FIGURE 47.2 Murphy’s Model The mo
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where k is the total number of crit
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FIGURE 47.5 Definition of IC critic
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distribution [34,35]: © 2002 by CR
Page 1334 and 1335:
and, in the case of w = X 2 − X 1
Page 1336 and 1337:
Algorithm • Input: a singly linke
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TRACIF takes a CIF file as input an
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TABLE 47.2 Critical Area Extraction
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Also, the critical areas for lithog
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(enhancement of the process cleanli
Page 1346 and 1347:
28. Corsi, F. and Martino, S., Defe
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U. Glaeser

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