1. Fundamentals of Computer Design

2. Outline Performance Evolution The Task of a Computer Designer
Technology and Computer Usage Trends
Cost and Trends in Cost
Measuring and Reporting Performance
Quantitative Principles of Computer Design

3. Computer Architecture Is …
The attributes of a [computing] system as seen by the programmer, i.e., the conceptual structure and functional behavior, as distinct from the organization of the data flows and controls, the logic design, and the physical implementation. (Amdahl, Blaaw, and Brooks, 1964)

4. Computer Architecture’s Changing Definition
1950s to 1960s: Computer Architecture Course
Computer Arithmetic
1970s to mid 1980s: Computer Architecture Course
Instruction Set Design, especially ISA appropriate for compilers.
[ISA includes Instruction set, word size, memory address, processor registers, address and data formats]
1990s to 2000s: Computer Architecture Course
Design of CPU, memory system, I/O system, Multiprocessors

5. Performance Evolution
1970s
– performance improved 25—30%/yr
Mostly due to improved architecture + some technology aids
1980s
VLSI + microprocessor became the foundation
Technology improves at 35%/yr
Mostly with UNIX and C in mid-80’s
Even most system programmers gave up assembly language
With this came the need for efficient compilers

6. Performance Evolution (Cont.)
1980s (Cont.)
Compiler focus brought on the great CISC vs. RISC debate
With the exception of Intel – RISC won the argument
RISC performance improved by 50%/year initially
Of course RISC is not as simple anymore and the compiler is a key part of the game
Does not matter how fast your computer is, if the compiler wastes most of it due to the inability to generate efficient code
With the exploitation of instruction-level parallelism (pipeline + super-scalar) and the use of caches, performance is further enhanced
CISC: Complex Instruction Set Computing
RISC: Relegate Important Stuff to the Compiler (Reduced Instruction Set Computing)

7. Growth in Performance (Figure 1.1)
MIPS: Microprocessor without Interlocked Pipeline
IBM: International Business Machines
Mainly due to advanced architecture ideas
HP: Hewlett Packard
DEC: Digital Equipment Corporation
Technology driven

8. The changing Face of Computing and the Task of the Computer Designer
Changes in computer use have led to three different computing markets
Each characterized by different applications, requirements, and computing technologies:
Desktop Computing
Servers
Embedded Computers

9. Desktop Computing
The first, and still the largest market in dollar terms, is desktop computing.
Desktop top systems often are where the newest, highest-performance ,microprocessors appear.
Recently cost-reduced microprocessors and systems appear.

10. Servers For servers different characteristics are important:
Availability
Which means that the system can reliably and effectively provide service.
Scalability
Means server systems often grow over their lifetime in response to a growing demand for the services they support (or) an increase in functional requirements.
The ability to scale up the computing capacity, the memory, the storage and the I/O bandwidth of server.
Efficient Throughput
That is, the overall performance of the server, in terms of transactions per minute or web page served per second.

11. Embedded Computers
Embedded computers have the widest range of processing power and cost.
Performance requirement in an embedded application is a real –time requirement.
A real-time performance requirement is one where a segment of the application has an absolute maximum execution time that is allowed.
Two other key characteristics exist in many embedded applications:
The need to minimize memory
The need to minimize power.

12. The Task of A Computer Designer

13. The Task of A Computer Designer
The task of computer designer faces is a complex one:
Determine what attributes are important for a new machine.
Then design a machine to maximize performance.
This aspects, including
Instruction set design
Functional Organization
Logic design and implementation

14. Condt…
Instruction set architecture refers to the actual programmer-visible instruction set.
The instruction set architecture servers as the boundary between the software and hardware.
The term Organization includes the high-level aspects of a computer design, such as
The Memory system,
The bus structure and
Design of the internal CPU
(CPU-where arithmetic, logic, branching, and data transfer are implemented)

15. Condt…..
Hardware is used to refer to the specifics of a machine, including:
The detailed logic design
The packaging technology of the machine.
Computer architects must design a computer to meet functional requirements as well as price, power, and performance goal.
In addition to performance and cost, performance must be aware of important trends in both the implementation technology and the use of computers.

16. Technology Trends

17. Technology Trends
To plan for the evolution of a machine, the designer must be especially aware of rapidly occurring changes in implementation technology.
4 implementation technologies, which change at a dramatic pace, are critical to modern implementations:
Integrated Circuit Logic Technology
Semiconductor DRAM
Magnetic disk Technology
Network Technology

18. Technology Trends (Cont..)
Integrated Circuits
Density increases at 35%/yr.
Die size increases 10%-20%/yr
Combination is a chip complexity growth rate of 55%/yr
Transistor speed increase is similar but signal propagation does not track this curve - so clock rates don’t go up as fast
Semiconductor DRAM
Density quadruples every 3 years (approx. 60%/yr) [4x steps]
Cycle time decreases slowly - 33% in 10 years
Interface changes have improved bandwidth

19. Technology Trends (Cont.)
Magnetic Disk
Currently density improves at 100%/yr
Access time has improved by 33% in 10 years
Network Technology
Depends both on the performance of switches and transmission system
1GB Ethernet becomes available about 5 years after 100MB
Doubling in bandwidth every year

20. Cost, Price, and Their Trends

21. Cost Clearly a market place issue -- profit as a function of volume
Price is what you sell a finished good for, and Cost is the amount spent to produce it.
Let’s focus on hardware costs
Factors impacting cost
Learning curve – manufacturing costs decrease over time
Yield – the percentage of manufactured devices that survives the testing procedure
Volume is also a key factor in determine cost
Commodities are products that are sold by multiple vendors in large volumes and are essentially identical.

22. Integrated Circuits Costs

23. Remember This Comic…?

24. Cost of an Integrated Circuit
The cost of a packaged integrated circuit is
Cost of die+Cost of testing die+Cost of packaging and final test
Cost of IC=
Final test yield
Cost of die=(Cost of wafer) / (Dies per wafer  Die yield)
  (Wafer diameter/2)   Wafer diameter
Dies per wafer=
Die area (2  Die area) 0.5

25. Cost of an Integrated Circuit
The fraction or percentage of good dies on a wafer number (die yield):
Defects per unit area  Die area -
Die yield=Wafer yield  { } 
Where  is a parameter that corresponds roughly to the number of masking level, a measure on manufacturing complexity, critical to die yield ( = 4.0 is a good estimate).
Die Cost goes roughly with die area5

26. Cost versus Price
The relationship between price and volume can increase the impact of changes in cost, especially at the low end of the market.
Factors determine price, and to typical ranges for these factors:
Direct Costs (add 10% to 30%): costs directly related to making a project
Labor, purchasing, scrap, warranty
Gross Margin (add 10% to 45%): the company’s overhead that cannot be billed directly to one project
R&D, marketing, sales, equipment maintenance, rental, financing cost, pretax profits, taxes
Average Discount to get List Price (add 33% to 66%)
Volume discounts and/or retailer markup

27. Cost/Price Illustration

28. Cost/Price for Different Kinds of Systems

29. Measuring and Reporting Performance

30. Performance When we can say that one computer is faster than another?
The user of a desktop machine may say a computer is faster when a program runs in less time.
The computer center manger running a large server system 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 large data processing center may be interested in increasing throughput.
[The total amount of work done in given time].

31. Performance (Cont.)
If we want to relate the performance of 2 different machines X and Y.
In particular “X is n times faster than Y” which means
Execution time is the reciprocal of performance.
i. e performance = 1/execution time
Improved performance  decreasing execution time

32. Measuring Performance
Several kinds of time
Wall-clock time: response time, or elapsed time
[which is the latency to complete a task, including
Disk access, memory access, input/output activities, operating systems overhead.
CPU time
CPU time can be further divided into the
User CPU time: CPU time spent in the program
System CPU time: CPU time spent in the operating system performing tasks requested by the program.

33. Choosing Programs to Evaluate Performance
Real applications – clearly the right choice
Porting and eliminating system-dependent activities
User burden -- to know which of your programs you really care about
Modified (or scripted) applications
Enhance portability or focus on particular aspects of system performance
Kernels – small, key pieces of real programs
Best used to isolate performance of individual features to explain the reasons from differences in performance of real programs
Not real programs however -- no user really uses them

34. Choosing Programs to Evaluate Performance (Cont.)
Toy benchmarks – quicksort, puzzle
Beginning programming assignment
Synthetic benchmarks
Try to match the average frequency of operations and operands of a large set of programs
No user really runs them -- not even pieces of real programs
They typically reside in cache & don’t test memory performance
At the very least you must understand what the benchmark code is in order to understand what it might be measuring
Companies thrive or bust on benchmark performance
Hence they optimize for the benchmark

35. Benchmark Suites
One of the most successful attempts to create standardized benchmarks application suits has been the SPEC.
SPEC (Standard Performance Evaluation Corporation)
Desktop benchmarks
Server benchmarks
Embedded benchmarks

36. Reporting Performance Results
The guiding principle of reporting performance measurements should be reproducibility
List everything another experimenter would need to duplicate the results.
A SPEC benchmark report requires a fairly complete descriptions of the machine and the compiler flags, as well as the publication of the both the baseline and optimized results.

37. Quantitative Principles of Computer Design

38. Make the Common Case Fast
Most pervasive principle of design is to make the common case fast.
In making a design trade-off, favor the frequent case over the infrequent case.
Improving the frequent event, rather than the rare event, will obviously help performance
The frequent case is simpler and can be done faster than the infrequent case.
Ex:
adding two numbers in the CPU, we can expect the overflow in the rare cases.
Therefore improve the performance by optimizing the more common case of no overflow.

39. Amdahl’s Law
To calculate the performance that can be obtained by improving some portion of computer.
It states that the performance improvement to be gained from using some faster mode of execution is limited by the fraction of the time the faster mode can be used.
It also defines the speed up that can be gained by using a particular feature,

40. Amdahl’s Law (Condt…) Defines speedup gained from a particular feature
Depends on 2 factors
Fraction of original computation time that can take advantage of the enhancement
Level of improvement gained by the feature
Amdahl’s law

41. Simple Example Amdahl’s Law says nothing about cost
Important Application:
FPSQRT 20%
FP instructions account for 50%
Other 30%
Designers say same cost to speedup:
FPSQRT by 40x
FP by 2x
Other by 8x
Which one should you invest?
Straightforward plug in the numbers & compare BUT what’s your guess??

42. And the Winner Is…?

43. Calculating CPU Performance
Essentially all computers are constructed using a clock running at a constant rate.
These discrete time events are called tricks, clock tricks, clock periods, clocks, cycles, or clock cycles.
CPU time for a program can be expressed 2 ways:

44. Calculating CPU Performance (Cont.)
In addition to the number of clock cycles needed to execute a program, we can also count the number of instructions executed.
The instruction path length or instruction count (IC).
Now we can calculate the average number of cycles per instruction (CPI).

45. Calculating CPU Performance (Cont.)
As the formula demonstrates, CPU performance Focus on 3 Factors -- Cycle Time, CPI, IC
Sadly - they are interdependent and making one better often makes another worse (but small or predictable impacts)
Cycle time depends on Hardware technology and organization
CPI depends on organization (pipeline, caching...) and ISA
IC depends on ISA and compiler technology
Often CPI’s are easier to deal with on a per instruction basis

46. Calculating CPU Performance (Cont.)
Some times it is useful in designing the CPU to calculate the number of total CPU cycles as