探索计算机组成原理：历史、设计与技术趋势

需积分: 34 117 浏览量更新于2024-07-27 1 收藏 4.82MB PDF 举报

《计算机组成原理》英文版是一本深入探讨现代计算机设计基础和技术趋势的教科书。该书首先在第一章“Fundamentals of Computer Design”中介绍了计算机设计师的角色，他们肩负着将先进技术转化为实用、高效的计算设备的任务。章节1.2详述了这个任务，强调了设计者需理解和掌握如何平衡性能、成本和易用性。随着时代的进步，1.3节讲述了技术与计算机使用趋势之间的关系，指出半个世纪以来，计算机技术经历了翻天覆地的变化，存储程序计算机的发展为现代个人电脑奠定了基础。作者通过对比1945年和1965年的技术水平，突显了技术进步的速度和规模。 1.4和1.5部分重点关注成本问题，讨论了随着时间推移，硬件成本的下降以及衡量和报告性能的标准变化。这些章节有助于读者理解技术进步如何影响计算机系统的性价比。在关键的1.6章，“Quantitative Principles of Computer Design”，作者深入讲解了计算机设计中的量化原则，如处理器速度、内存容量和能效等核心概念，这些都是决定系统效能的关键因素。第1.7章引入了“Memory Hierarchy”概念，这是计算机架构中的重要组成部分，它解释了为何不同层次的存储器（如寄存器、缓存、主存和硬盘）被设计成有层次结构，以优化数据访问速度和存储效率。 1.8节则揭示了设计过程中可能出现的误解和陷阱，提醒读者在追求性能提升时需要注意的问题。这部分内容对避免设计误区至关重要。 1.9“Concluding Remarks”总结了前面章节的主要内容，并展望了未来可能的发展方向，同时提供了历史视角和参考文献，帮助读者将当前知识置于更广阔的背景中。最后，附录的“Exercises”提供了实践性的学习机会，鼓励读者通过解决实际问题来巩固理论知识，确保了理论与实践的紧密结合。《计算机组成原理》英文版是一本既涵盖了技术变迁又注重设计原则的教材，对于理解计算机硬件和系统设计的发展脉络，以及如何在这个快速发展的领域保持创新和效率具有重要价值。

1.4 Cost and Trends in Cost

before it becomes price, and the computer designer should understand how a de-

sign decision will affect the potential selling price. For example, changing cost

by $1000 may change price by $3000 to $4000. Without understanding the rela-

tionship of cost to price the computer designer may not understand the impact on

price of adding, deleting, or replacing components. The relationship between

price and volume can increase the impact of changes in cost, especially at the low

end of the market. Typically, fewer computers are sold as the price increases. Fur-

thermore, as volume decreases, costs rise, leading to further increases in price.

Thus, small changes in cost can have a larger than obvious impact. The relation-

ship between cost and price is a complex one with entire books written on the

subject. The purpose of this section is to give you a simple introduction to what

factors determine price and typical ranges for these factors.

The categories that make up price can be shown either as a tax on cost or as a

percentage of the price. We will look at the information both ways. These differ-

ences between price and cost also depend on where in the computer marketplace

a company is selling. To show these differences, Figures 1.7 and 1.8 on page 16

show how the difference between cost of materials and list price is decomposed,

with the price increasing from left to right as we add each type of overhead.

Direct costs

refer to the costs directly related to making a product. These in-

clude labor costs, purchasing components, scrap (the leftover from yield), and

warranty, which covers the costs of systems that fail at the customer’s site during

the warranty period. Direct cost typically adds 20% to 40% to component cost.

Service or maintenance costs are not included because the customer typically

pays those costs, although a warranty allowance may be included here or in gross

margin, discussed next.

The next addition is called the

gross margin

, the company’s overhead that can-

not be billed directly to one product. This can be thought of as indirect cost. It in-

cludes the company’s research and development (R&D), marketing, sales,

manufacturing equipment maintenance, building rental, cost of ﬁnancing, pretax

proﬁts, and taxes. When the component costs are added to the direct cost and

gross margin, we reach the

average selling price—ASP in the language of

MBAs—the money that comes directly to the company for each product sold.

The gross margin is typically 20% to 55% of the average selling price, depending

on the uniqueness of the product. Manufacturers of low-end PCs generally have

lower gross margins for several reasons. First, their R&D expenses are lower.

Second, their cost of sales is lower, since they use indirect distribution (by mail,

phone order, or retail store) rather than salespeople. Third, because their products

are less unique, competition is more intense, thus forcing lower prices and often

lower proﬁts, which in turn lead to a lower gross margin.

List price and average selling price are not the same. One reason for this is that

companies offer volume discounts, lowering the average selling price. Also, if the

product is to be sold in retail stores, as personal computers are, stores want to

keep 40% to 50% of the list price for themselves. Thus, depending on the distri-

bution system, the average selling price is typically 50% to 75% of the list price.

1.4 Cost and Trends in Cost 17

As we said, pricing is sensitive to competition: A company may not be able to

sell its product at a price that includes the desired gross margin. In the worst case,

the price must be signiﬁcantly reduced, lowering gross margin until proﬁt be-

comes negative! A company striving for market share can reduce price and proﬁt

to increase the attractiveness of its products. If the volume grows sufﬁciently,

costs can be reduced. Remember that these relationships are extremely complex

and to understand them in depth would require an entire book, as opposed to one

section in one chapter. For example, if a company cuts prices, but does not obtain

a sufﬁcient growth in product volume, the chief impact will be lower proﬁts.

Many engineers are surprised to ﬁnd that most companies spend only 4% (in

the commodity PC business) to 12% (in the high-end server business) of their in-

come on R&D, which includes all engineering (except for manufacturing and

ﬁeld engineering). This is a well-established percentage that is reported in com-

panies’ annual reports and tabulated in national magazines, so this percentage is

unlikely to change over time.

The information above suggests that a company uniformly applies ﬁxed-

overhead percentages to turn cost into price, and this is true for many companies.

But another point of view is that R&D should be considered an investment. Thus

an investment of 4% to 12% of income means that every $1 spent on R&D should

lead to $8 to $25 in sales. This alternative point of view then suggests a different

gross margin for each product depending on the number sold and the size of the

investment.

Large, expensive machines generally cost more to develop—a machine cost-

ing 10 times as much to manufacture may cost many times as much to develop.

Since large, expensive machines generally do not sell as well as small ones, the

gross margin must be greater on the big machines for the company to maintain a

proﬁtable return on its investment. This investment model places large machines

in double jeopardy—because there are fewer sold and they require larger R&D

costs—and gives one explanation for a higher ratio of price to cost versus smaller

machines.

The issue of cost and cost/performance is a complex one. There is no single

target for computer designers. At one extreme, high-performance design spares

no cost in achieving its goal. Supercomputers have traditionally ﬁt into this cate-

gory. At the other extreme is low-cost design, where performance is sacriﬁced to

achieve lowest cost. Computers like the IBM PC clones belong here. Between

these extremes is cost/performance design, where the designer balances cost ver-

sus performance. Most of the workstation manufacturers operate in this region. In

the past 10 years, as computers have downsized, both low-cost design and cost/

performance design have become increasingly important. Even the supercom-

puter manufacturers have found that cost plays an increasing role. This section

has introduced some of the most important factors in determining cost; the next

section deals with performance.

18 Chapter 1 Fundamentals of Computer Design

When we say one computer is faster than another, what do we mean? The com-

puter user may say a computer is faster when a program runs in less time, while

the computer center manager may say a computer is faster when it completes

more jobs in an hour. The computer user is interested in reducing response

time—the time between the start and the completion of an event—also referred to

as execution time. The manager of a large data processing center may be interest-

ed in increasing throughput—the total amount of work done in a given time.

In comparing design alternatives, we often want to relate the performance of

two different machines, say X and Y. The phrase “X is faster than Y” is used here

to mean that the response time or execution time is lower on X than on Y for the

given task. In particular, “X is n times faster than Y” will mean

Since execution time is the reciprocal of performance, the following relationship

holds:

n = = =

The phrase “the throughput of X is 1.3 times higher than Y” signiﬁes here that

the number of tasks completed per unit time on machine X is 1.3 times the num-

ber completed on Y.

Because performance and execution time are reciprocals, increasing perfor-

mance decreases execution time. To help avoid confusion between the terms

increasing and decreasing, we usually say “improve performance” or “improve

execution time” when we mean increase performance and decrease execution

time.

Whether we are interested in throughput or response time, the key measure-

ment is time: The computer that performs the same amount of work in the least

time is the fastest. The difference is whether we measure one task (response time)

or many tasks (throughput). Unfortunately, time is not always the metric quoted

in comparing the performance of computers. A number of popular measures have

been adopted in the quest for a easily understood, universal measure of computer

performance, with the result that a few innocent terms have been shanghaied

from their well-deﬁned environment and forced into a service for which they

were never intended. The authors’ position is that the only consistent and reliable

measure of performance is the execution time of real programs, and that all pro-

posed alternatives to time as the metric or to real programs as the items measured

1.5

Measuring and Reporting Performance

Execution time

----------------------------------------

Execution time

----------------------------------------

Performance

----------------------------------

Performance

----------------------------------

-----------------------------------

Performance

----------------------------------

1.5 Measuring and Reporting Performance 19

have eventually led to misleading claims or even mistakes in computer design.

The dangers of a few popular alternatives are shown in Fallacies and Pitfalls,

section 1.8.

Measuring Performance

Even execution time can be deﬁned in different ways depending on what we

count. The most straightforward deﬁnition of time is called wall-clock time, re-

sponse time, or elapsed time, which is the latency to complete a task, including

disk accesses, memory accesses, input/output activities, operating system over-

head—everything. With multiprogramming the CPU works on another program

while waiting for I/O and may not necessarily minimize the elapsed time of one

program. Hence we need a term to take this activity into account. CPU time rec-

ognizes this distinction and means the time the CPU is computing, not including

the time waiting for I/O or running other programs. (Clearly the response time

seen by the user is the elapsed time of the program, not the CPU time.) CPU time

can be further divided into the CPU time spent in the program, called user CPU

time, and the CPU time spent in the operating system performing tasks requested

by the program, called system CPU time.

These distinctions are reﬂected in the UNIX time command, which returns

four measurements when applied to an executing program:

90.7u 12.9s 2:39 65%

User CPU time is 90.7 seconds, system CPU time is 12.9 seconds, elapsed time is

2 minutes and 39 seconds (159 seconds), and the percentage of elapsed time that

is CPU time is (90.7 + 12.9)/159 or 65%. More than a third of the elapsed time in

this example was spent waiting for I/O or running other programs or both. Many

measurements ignore system CPU time because of the inaccuracy of operating

systems’ self-measurement (the above inaccurate measurement came from UNIX)

and the inequity of including system CPU time when comparing performance be-

tween machines with differing system codes. On the other hand, system code on

some machines is user code on others, and no program runs without some operat-

ing system running on the hardware, so a case can be made for using the sum of

user CPU time and system CPU time.

In the present discussion, a distinction is maintained between performance

based on elapsed time and that based on CPU time. The term system performance

is used to refer to elapsed time on an unloaded system, while CPU performance

refers to user CPU time on an unloaded system. We will concentrate on CPU per-

formance in this chapter.

剩余911页未读，继续阅读

YALE_XYZ

粉丝: 0

探索计算机组成原理：历史、设计与技术趋势

中山大学计算机组成原理课本习题答案

桂电计算机组成原理课本答案与复习重点

计算机组成原理课本第八版的答案

计算机组成原理课本答案

组成原理课本答案第五版.pdf

计算机组成原理课本pdf

大二课本计算机组成原理

机械原理课本

计算机组成原理(唐朔飞)课本及课后答案

山东大学计算机组成原理资料（课本答案，考试题，复习资料）

最新资源