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9. Espasa, R., Advanced Vector Architectures, Ph.D. Thesis, Universitat Politecnica de Catalunya, Barcelona, 1997. 10. Asanovic, K., Vector Microprocessors, Ph.D. Thesis, University of California, Berkeley, 1998. 5.4 Multithreading, Multiprocessing Manoj Franklin Introduction A defining challenge for research in computer science and engineering has been the ongoing quest for faster execution of programs. There is broad consensus that barring the use of novel technologies such as quantum computing and biological computing, the key to further progress in this quest is to do parallel processing of some kind. The commodity microprocessor industry has been traditionally looking to fine-grained or instruction level parallelism (ILP) for improving performance, with sophisticated microarchitectural techniques (such as pipelining, branch prediction, out-of-order execution, and superscalar execution) and sophisticated compiler optimizations. Such hardware-centered techniques appear to have scalability problems in the sub-micron technology era and are already appearing to run out of steam. According to a recent position paper by Dally and Lacy [4], “Over the past 20 years, the increased density of VLSI chips was applied to close the gap between microprocessors and high-end CPUs. Today this gap is fully closed and adding devices to uniprocessors is well beyond the point of diminishing returns.” We view ILP as the main success story form of parallelism thus far, as it was adopted in a big way in the commercial world for reducing the completion time of general purpose applications. The future promises to expand the “parallelism bridgehead” established by ILP with the “ground forces” of thread-level parallelism (TLP), by using multiple processing elements to exploit both fine-grained and coarse-grained parallelism in a natural way. Current hardware trends are playing a driving role in the development of multiprocessing techniques. Two important hardware trends in this regard are single chip transistor count and clock speed, both of which have been steadily increasing due to advances in sub-micron technology. The Semiconductor Industry Association (SIA) has predicted that by 2012, industry will be manufacturing processors containing 1.4 billion transistors and running at 10 GHz [39]. DRAMs will grow to 4 Gbits in 2003. This increasing transistor budget has opened up new opportunities and challenges for the development of on-chip multiprocessing. One of the challenges introduced by sub-micron technology is that wire delays become more important than gate delays [39]. This effect is predominant in global wires because their length depends on the die size, which is steadily increasing. An important implication of the physical limits of wire scaling is that, the area that is reachable in a single clock cycle of future processors will be confined to a small portion of the die [39]. A natural way to make use of the additional transistor budget and to deal with the wire delay problem is to use the concept of multithreading or multiprocessing 1 in the processor microarchitecture. That is, build the processor as a collection of independent processing elements (PEs), each of which executes a separate thread or flow of control. By designing the processor as a collection of PEs, (a) the number of global wires reduces, and (b) very little communication occurs through global wires. Thus, much of the communication occurring in the multi-PE processor is local in nature and occurs through short wires. In the recent past, several multithreading proposals have appeared in the literature. A few commercial processors have already started implementing some of these multithreading concepts in a single chip [24,34]. Although the underlying theme behind the different proposals is quite similar, the exact manner in which they perform multithreading is quite different. Each of the methodologies has different hardware 1 In this section, we use the terms multithreading, multiprocessing, and parallel processing interchangeably. Similarly, we use the generic term threads whenever the context is applicable to processes, light-weight processes, and lightweight threads. © 2002 by CRC Press LLC
and software requirements and trade-offs. The objective of this chapter is to present a common framework for studying different multiprocessing and multithreading techniques, and to discuss existing multithreaded processors and futuristic proposals in the light of this framework. The following are some of the questions that are specifically addressed in the common framework: • Parallel programming model • Nature of threads • PE Interconnects • Role of the compiler The introduction section has highlighted the importance of multithreading and multiprocessing. The rest of this chapter is organized as follows. The section on “Parallel Processing Software Framework” presents a common framework for studying different multithreading and multiprocessing approaches, and highlights software issues that are important to consider while examining them. The section on “Parallel Processing Hardware Framework” presents a common framework for studying parallel processor hardware configurations. The “Concluding Remarks” section provides a survey of existing multithreaded processors and proposals. In particular, it describes how multithreading is employed in the multiscalar processor, the superthreaded processor, the trace processor, the M-machine, and some of the other multithreaded microarchitectures. Finally, “Concluding Remarks” presents a qualitative comparison and discusses future trends. Parallel Processing Software Framework In this section we discuss our framework for studying multithreading and multiprocessing. We also identify three key issues related to multithreading: thread granularity, parallel programming model, and program partitioning into threads. We shall discuss each of these issues in detail. Not all of these issues are entirely orthogonal to each other, and it is our objective to highlight how each issue bears on other related issues. We define a thread as a flow of control through a program and that flow’s current state (represented by a current program counter, a call/return stack and, occasionally, some thread-private data). The central idea behind multithreading and multiprocessing is to have multiple flows of control within a process, allowing parts of the process to be executed in parallel. A process can have one or more threads doing its work. Threads that execute in parallel are invariably control-independent, in which case the decision to execute a thread does not depend on the other active threads. Thus, instructions that are controldependent on a conditional branch invariably belong to the thread to which that branch belongs. Parallel Programming Model An important attribute of any multiprocessing/multithreading system is its parallel programming model, embodied in a parallel language or programming environment. This model specifies the names (such as registers and memory addresses) the thread can access, the operations it can perform on the named data, and the ordering semantics among these operations, particularly those done by distinct threads. (In the simplest case, the model assumes multiprogramming, which has no inter-thread communication and synchronization.) First, we will discuss thread sequencing model, which specifies ordering constraints (if any) on multiple threads. Then, we discuss inter-thread communication, which deals with passing data values among two or more threads. Finally, we discuss synchronization aspects of the programming model, which cause running threads to wait for one another, and waiting threads to resume execution at the proper time. Orchestrating the inter-thread ordering often requires explicit synchronization operations when the ordering implicit in the basic operations is not sufficient. Thread Granularity and Management Thread-level parallelism (TLP) is more coarse-grained than ILP, and has wide variance in granularity. We categorize the TLP granularities into three levels as described below. Depending on the granularity, © 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
Page 136 and 137: John C. McCallum National Universit
Page 138 and 139: enchmark took between 15.7 and 5115
Page 140 and 141: The improvements in line widths, ch
Page 142 and 143: performance. Extensive lists of SPE
Page 144 and 145: TABLE 4.6 Functions of Memory and S
Page 146 and 147: Memory Price ($/MB) FIGURE 4.3 Cost
Page 148 and 149: TABLE 4.8 Disk Drive Characteristic
Page 150 and 151: 4.6 Summary The performance of comp
Page 152 and 153: 53. Curnow, H. J., and Wichmann, B.
Page 154 and 155: Computer Systems and Architecture
Page 156 and 157: advances that have been made in dev
Page 158 and 159: Server Types Servers are optimized
Page 160 and 161: Total Cost of Ownership Another con
Page 162 and 163: edundant memory-bit steering, and s
Page 164 and 165: majority of the users. Hardware opt
Page 166 and 167: processor implementations. In later
Page 168 and 169: FIGURE 5.7 an operand. For larger c
Page 170 and 171: Example 2 This example contrasts th
Page 172 and 173: Unlike the Defoe, the IA-64 archite
Page 174 and 175: This 3-phase approach fails to expl
Page 176 and 177: 6. Scott Rixner, William J. Dally,
Page 178 and 179: Shared-memory vector architectures
Page 180 and 181: The vector ISA usually fixes the ma
Page 182 and 183: FIGURE 5.12 A vector unit construct
Page 184 and 185: use of loops optimized for certain
Page 188 and 189: thread management (including run-ti
Page 190 and 191: In the message passing model, inter
Page 192 and 193: multithreaded hardware, possibly by
Page 194 and 195: synchronization) and usually contai
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Page 198 and 199: FIGURE 5.16 When a load request is
Page 200 and 201: list a few helpful references to wh
Page 202 and 203: 38. S. Wallace, B. Calder, and D. T
Page 204 and 205: Of course, SIMD machines have limit
Page 206 and 207: computation, it will decrease execu
Page 208 and 209: FIGURE 5.19 An 8 × 8 baseline netw
Page 210 and 211: Since then, we have seen constant e
Page 212 and 213: Stack: Data: Text: Virtual Space FI
Page 214 and 215: FIGURE 5.25 Shared memory. Shared m
Page 216 and 217: 0 2 GB Text Init. Data Bss Heap . .
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
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Thus, the maximal number of instruc
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In addition, if rename buffers are
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it, whose role will be explained su
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As Fig. 6.13 shows, the latest proc
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for recovery. Both processors incor
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FIGURE C. The principle of direct i
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13. White, S. and Reysa, J., PowerP
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FIGURE 6.14 A branch flowing throug
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is that mispredictions limit the pr
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fetch engine to identify which inst
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FIGURE 6.17 A schematic for a bimod
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FIGURE 6.20 A schematic for a GAg g
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FIGURE 6.22 A schematic for a hybri
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time this branch is seen, those bit
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FIGURE 6.23 Branch prediction accur
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11. Price, C., MIPS IV Instruction
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transporting digital bits, whereas
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FIGURE 6.25 The system architecture
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Finally, because the main task of n
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Pradip Bose IBM T. J. Watson Resear
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frequency © 2002 by CRC Press LLC
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The “mips” metric for performan
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Hence, in this paper, we do not dwe
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FIGURE 7.4 Parallel SIMD architectu
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dynamic prediction of such idle mod
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FIGURE 7.7 High-level block-diagram
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(measured as a performance over pow
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Steady-state BIPS FIGURE 7.9 Perfor
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8. Larson, A. G., “Cost-effective
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Jozo J. Dujmović San Francisco Sta
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x FIGURE 8.1 Movement of the disk I
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The critical distance x ∗ is Ther
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Hence, the average seek time for th
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FIGURE 8.4 Four-parameter exponenti
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Access Time [ms] 2 0 0 FIGURE 8.6 M
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TABLE 8.1 Classification of Eight B
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The traditional load independent me
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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
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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
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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
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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
Page 1342 and 1343:
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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