Download 02 Computer Evolution and Performance

Computer Organization and Architecture
William Stallings
8th Edition
Chapter 2
Computer Evolution and Performance
BRIEF HISTORY OF COMPUTERS
The First Generation: Vacuum Tubes
ENIAC - background
• Electronic Numerical Integrator And Computer
• Eckert and Mauchly proposed to build a generalpurpose computer using vacuum tubes for the BRL’s
application.
• At university of Pennsylvania
• It was the world’s first general purpose electronic
digital computer.
• Started 1943
• Finished 1946
▫ Too late for war effort
• Used until 1955
ENIAC - details
• The ENIAC was a decimal rather than a binary
machine. Numbers were represented in decimal
form, and arithmetic was performed in the decimal
system.
• Its memory consisted of 20 accumulators of 10 digits
number.
• It had to be programmed manually by setting
switches and plugging and unplugging cables.
• The resulting machine was enormous, weighing 30
tons, occupying 1500 square feet of floor space, and
containing more than 18,000 vacuum tubes.
ENIAC - details
• When operating, it consumed 140 kilowatts of power.
• It was also substantially
electromechanical computer,
additions per second.
faster than any
capable of 5000
Von Neumann/Turing
• The idea is a computer could get its instructions
by reading them from memory, and a program
could be set or altered by setting the values of a
portion of memory.
• This idea, known as the stored-program
concept.
• The first publication of the idea was in a 1945
proposal by von Neumann for a new computer,
the EDVAC (Electronic Discrete Variable
Computer).
Von Neumann/Turing
• In 1946, von Neumann and his colleagues began the
design of a new stored program computer, referred
to as the IAS computer, at the Princeton Institute
for Advanced Studies.
• The general structure of the IAS computer consists
of:
▫ Main memory stores data and instructions
▫ Arithmetic and logic unit (ALU) capable of operating
on binary data.
▫ Control unit (CU) interprets instructions in memory
to be executed.
▫ Input and output (I/O) equipment operated by the
control unit.
1
• Completed 1952.
Structure of The IAS Computer
• all of today’s computers have this same general
structure and function and are thus referred to as von
Neumann machines.
IAS Memory Formats:
• The memory of the IAS consists of 1000 storage locations,
called words, of 40 binary digits (bits) each.
• Both data and instructions are stored there.
• Numbers are represented in binary form, and each
instruction is a binary code.
• Each number is represented by a sign bit and a 39-bit
value.
• A word may also contain two 20-bit instructions, with
each instruction consisting of an 8-bit operation code
(opcode) specifying the operation to be performed and a
12-bit address designating one of the words in memory
(numbered from 0 to 999).
IAS Memory Formats
Structure of IAS Computer
• The control unit operates the IAS by fetching
instructions from memory and executing them one
at a time.
• Both the control unit and the ALU contain storage
locations, called registers, defined as follows:






Memory buffer register (MBR).
Memory address register (MAR).
Instruction register (IR).
Instruction buffer register (IBR).
Program counter (PC).
Accumulator (AC) and multiplier quotient (MQ)
• Memory buffer register (MBR) contains a word to be
stored in memory or sent to the I/O unit, or is used to
receive a word from memory or from the I/O unit.
• Memory address register (MAR) specifies the address
in memory of the word to be written from or read into
the MBR.
• Instruction register (IR) contains the 8-bit opcode
instruction being executed.
• Instruction buffer register (IBR) holds temporarily the
right hand instruction from a word in memory.
• Program counter (PC) contains the address of the
next instruction-pair to be fetched from memory.
• Accumulator (AC) and multiplier quotient (MQ)
hold temporarily operands and results of ALU
operations.
• Next figure is to display the expanded structure of
IAS Computer.
IAS - details
• 1000 x 40 bit words
▫ Binary number
▫ 2 x 20 bit instructions
• Set of registers (storage in CPU)
▫
▫
▫
▫
▫
▫
▫
Memory Buffer Register
Memory Address Register
Instruction Register
Instruction Buffer Register
Program Counter
Accumulator
Multiplier Quotient
• The IAS operates by repetitively performing
an instruction cycle, each instruction cycle
consists of two subcycles: fetch cycle and
execution cycle.
IAS Computer Instructions
• The IAS computer had a total of 21 instructions, which are
grouped as follows:
• Data transfer: Move data between memory and ALU registers or
between two ALU registers.
• Unconditional branch: Normally, the control unit executes
instructions in sequence from memory. This sequence can be
changed by a branch instruction, which facilitates repetitive
operations.
• Conditional branch: The branch can be made dependent on a
condition, thus allowing decision points.
• Arithmetic: Operations performed by the ALU.
• Address modify: Permits addresses to be computed in the ALU
and then inserted into instructions stored in memory. This allows a
program considerable addressing flexibility.
The Second Generation
Transistors
• The first major change in the electronic computer came with
the replacement of the vacuum tube by the transistor.
• The transistor is smaller, cheaper, and dissipates less heat
than a vacuum tube, but can be used in the same way as a
vacuum tube to construct computers.
• Unlike the vacuum tube, which requires wires, metal plates, a
glass capsule, and a vacuum, the transistor is a solid-state
device, made from silicon.
• It was invented in 1947 at Bell Labs.
Transistor Based Computers
• The use of the transistor defines the second generation of
computers.
• IBM again was not the first company to deliver the new
technology. NCR and RCA were the front-runners with some
small transistor machines.
• IBM followed shortly with the 7000 series.
• The second generation is noteworthy also for the appearance
of the Digital Equipment Corporation (DEC).
• DEC was founded in 1957 and, in that year, delivered its
first computer which is called the PDP-1.
The Third Generation
Integrated Circuits - Microelectronics
• In 1958 came the achievement that revolutionized electronics
and started the era of microelectronics: the invention of the
integrated circuit.
• It is the integrated circuit that defines the third generation of
computers.
• Microelectronics means “small electronics.”
• Since the beginnings of digital electronics and the computer
industry, there has been a persistent and consistent trend
toward the reduction in size of digital electronic circuits.
• A computer is made up of gates, memory cells and
interconnections.
The Third Generation
Integrated Circuits - Microelectronics
• These can be manufactured on a semiconductor e.g. silicon
wafer.
• The basic elements of a digital computer must perform storage,
movement, processing, and control functions. Only two
fundamental types of components are required: gates and
memory cells.
• A gate is a device that implements a simple boolean or logical
function such as (AND gate).
• The memory cell is a device that can store one bit of data.
• By interconnecting large numbers of these fundamental
devices, we can construct a computer.
• We can relate this to our four basic functions as follows:
▫ Data storage: Provided by memory cells.
▫ Data processing: Provided by gates.
▫ Data movement: The paths among components are used to
move data from memory to memory and from memory
through gates to memory.
▫ Control: The paths among components can carry control
signals.
Fundamental Computer Elements
Generations of Computer
• Vacuum tube - 1946-1957
• Transistor - 1958-1964
• Small scale integration - 1965
▫ Up to 100 devices on a chip
• Medium scale integration - to 1971
▫ 100-3,000 devices on a chip
• Large scale integration (LSI) - 1971-1977
▫ 3,000 - 100,000 devices on a chip
• Very large scale integration (VLSI) - 1978 -1991
▫ 100,000 - 100,000,000 devices on a chip
• Ultra large scale integration (ULSI) - 1991
▫ Over 100,000,000 devices on a chip
Moore’s Law
•
•
•
•
•
•
•
•
•
Increased density of components on chip.
Gordon Moore – cofounder of Intel.
Number of transistors on a chip will double every year.
Since 1970’s development has slowed a little.
▫ Number of transistors doubles every 18 months.
Cost of a chip has remained almost unchanged.
Higher packing density means shorter electrical paths, giving
higher performance.
Smaller size gives increased flexibility.
Reduced power and cooling requirements.
Fewer interconnections increases reliability.
Growth in CPU Transistor Count
This figure reflects the famous Moore’s law.
IBM 360 series
• In 1964, IBM announced the System/360, a new family of
computer products.
• It was replaced and not compatible with 7000 series, so the
360 product line was incompatible with older IBM machines.
• First planned “family” of computers, the characteristics of the
family are as follows :
▫ Similar or identical instruction sets.
▫ Similar or identical O/S.
▫ Increasing speed.
▫ Increasing number of I/O ports (i.e. more terminals).
▫ Increased memory size.
▫ Increased cost.
• Multiplexed switch structure.
DEC PDP-8
• In1964, PDP-8 was appeared from Digital Equipment
Corporation (DEC).
• Small size and low cost.
• First minicomputer (after miniskirt!).
• Did not need air conditioned room.
• Small enough to sit on a lab bench.
• Cost $16,000, it was cheap enough for each lab technician to
have one.
▫ $100k+ for IBM 360
• Embedded
applications
manufacturers (OEM).
• Used bus structure.
and
original
equipment
DEC - PDP-8 Bus Structure
• The PDP-8 bus, called the Omnibus, consists of 96
separate signal paths, used to carry control, address, and
data signals.
Later Generations
Semiconductor Memory
• In 1970, Fairchild produced the first relatively
capacious semiconductor memory.
• It was about the size of a single core.
▫ i.e. 1 bit of magnetic core storage.
•
•
•
•
It holds 256 bits of memory.
Non-destructive read.
Much faster than core.
Capacity approximately doubles each year.
Speeding it up
•
•
•
•
•
•
Pipelining
On board cache
On board L1 & L2 cache
Branch prediction
Data flow analysis
Speculative execution
Performance Balance
• Processor speed increased
• Memory capacity increased
• Memory speed lags behind processor speed
Logic and Memory Performance Gap
Solutions
• Increase number of bits retrieved at one time
▫ Make DRAM “wider” rather than “deeper”
• Change DRAM interface
▫ Cache
• Reduce frequency of memory access
▫ More complex cache and cache on chip
• Increase interconnection bandwidth
▫ High speed buses
▫ Hierarchy of buses
I/O Devices
•
•
•
•
•
Peripherals with intensive I/O demands
Large data throughput demands
Processors can handle this
Problem moving data
Solutions:
▫
▫
▫
▫
▫
Caching
Buffering
Higher-speed interconnection buses
More elaborate bus structures
Multiple-processor configurations
Typical I/O Device Data Rates
Key is Balance
•
•
•
•
Processor components
Main memory
I/O devices
Interconnection structures
New Approach – Multiple Cores
• Multiple processors on single chip
▫ Large shared cache
• Within a processor, increase in performance proportional to
square root of increase in complexity
• If software can use multiple processors, doubling number of
processors almost doubles performance
• So, use two simpler processors on the chip rather than one
more complex processor
• With two processors, larger caches are justified
▫ Power consumption of memory logic less than processing logic
Embedded Systems ARM
• Embedded system. A combination of computer hardware and
software, and perhaps additional mechanical or other parts,
designed to perform a dedicated function. In many cases,
embedded systems are part of a larger system or product.
• An alternative approach to processor design in the reduced
instruction set computer (RISC).
• The ARM architecture is used in a wide variety of embedded
systems and is one of the most powerful and best-designed
RISC-based systems on the market.
Embedded Systems ARM
• The ARM architecture refers to a processor architecture that
has evolved from RISC design principles and is used in
embedded systems.
• ARM evolved from RISC design.
• Used mainly in embedded systems
▫ Used within product
▫ Not general purpose computer
▫ Dedicated function
▫ E.g. Anti-lock brakes in car
Embedded Systems Requirements
• Different sizes
▫ Different constraints, optimization, reuse
• Different requirements
▫
▫
▫
▫
▫
▫
▫
Safety, reliability, real-time, flexibility, legislation
Lifespan
Environmental conditions
Static v dynamic loads
Slow to fast speeds
Computation v I/O intensive
Discrete event v continuous dynamics
Possible Organization of an Embedded System
ARM Evolution
•
•
•
•
Designed by ARM Inc., Cambridge, England
Licensed to manufacturers
High speed, small die, low power consumption
PDAs, hand held games, phones
▫ E.g. iPod, iPhone
• Acorn produced ARM1 & ARM2 in 1985 and ARM3
in 1989
• Acorn, VLSI and Apple Computer founded ARM
Ltd.
ARM Systems Categories
• Embedded real time
• Application platform
▫ Linux, Palm OS, Symbian OS, Windows mobile
• Secure applications
Performance Assessment
Clock Speed
• Key parameters
▫ Performance, cost, size, security, reliability, power consumption
• System clock speed
•
•
•
•
▫ In Hz or multiples of
▫ Clock rate, clock cycle, clock tick, cycle time
Signals in CPU take time to settle down to 1 or 0
Signals may change at different speeds
Operations need to be synchronised
Instruction execution in discrete steps
▫ Fetch, decode, load and store, arithmetic or logical
▫ Usually require multiple clock cycles per instruction
• Pipelining gives simultaneous execution of instructions
• So, clock speed is not the whole story
System Clock
• clock signals are generated by a quartz crystal, which
generates a constant signal wave while power is applied.
This wave is converted into a digital voltage pulse stream
that is provided in a constant flow to the processor
circuitry.
Instruction Execution Rate
• Millions of instructions per second (MIPS)
• Millions of floating point instructions per second
(MFLOPS)
• Heavily dependent on instruction set, compiler
design, processor implementation, cache & memory
hierarchy
INSTRUCTION EXECUTION RATE
A processor is driven by a clock with a constant
frequency f or, equivalently, a constant cycle time T, where T= 1/f
Define the instruction count, Ic, for a program as the number of machine instructions
executed for that program until it runs to completion or for some defined time .
interval
Let CPI i be the number of cycles required
for instruction type i.
and Ii be the number of executed instructions of type I for a given program.
Then we can calculate an overall CPI as follows:
n

CPI =
(CPIi * Ii)
i 1
Ic
The processor time T needed to execute a given program
T = Ic * CPI * t
performance
A common measure of performance for a processor is the
rate at which instructions are executed, expressed as
millions of instructions per second (MIPS), referred
to as the MIPS rate.
We can express the MIPS rate in terms of
the clock rate and CPI as follows
MIPS rate =Ic /T * 106 = f / CPI * 106
performance
For example, consider the execution of a program which results in the execution
of 2 million instructions on a 400-MHz processor. The program consists of four
major types of instructions. The instruction mix and the CPI for each instruction
type are given below based on the result of a program trace experiment:
Instruction Type
Arithmetic and logic
Load/store with cache hit
Branch
Memory reference with cache miss
CPI
Instruction Mix
1
2
4
8
60%
18%
12%
10%
T = Ic * CPI * t
The average CPI when the program is executed on a uniprocessor with the
above trace results is CPI= 0.6 +(2 *0.18) +(4* 0.12) +(8 *0.1) =2.24.
The corresponding MIPS rate is =(400* 106) /(2.24 *106) =178.
MFLOPS
Another common performance measure deals
. Floating-point
performance is expressed as millions of floating-point operations per second
(MFLOPS), defined as follows only with floating-point instructions.
Number of executed floating-point operations in a program
MFLOPS = _______________________________________________
execution time * 106
Benchmarks
• Programs designed to test performance
• Written in high level language
▫ Portable
• Represents style of task
▫ Systems, numerical, commercial
• Easily measured
• Widely distributed
• E.g. System Performance Evaluation Corporation (SPEC)
▫ CPU2006 for computation bound
 17 floating point programs in C, C++, Fortran
 12 integer programs in C, C++
 3 million lines of code
▫ Speed and rate metrics
 Single task and throughput
SPEC Speed Metric
• Single task
• Base runtime defined for each benchmark using reference
machine
• Results are reported as ratio of reference time to system run
time
▫ Trefi execution time for benchmark i on reference machine
▫ Tsuti execution time of benchmark i on test system
• Overall performance calculated by averaging ratios for all 12
integer benchmarks
— Use geometric mean
– Appropriate for normalized numbers such as ratios
,
, ∏xi = x1∙x2∙...∙xn
SPEC Rate Metric
• Measures throughput or rate of a machine carrying out a
number of tasks
• Multiple copies of benchmarks run simultaneously
▫ Typically, same as number of processors
• Ratio is calculated as follows:
▫ Trefi reference execution time for benchmark i
▫ N number of copies run simultaneously
▫ Tsuti elapsed time from start of execution of program
on all N processors until completion of all copies of
program
▫ Again, a geometric mean is calculated
Amdahl’s Law
• Gene Amdahl [AMDA67]
• Potential speed up of program using multiple processors
• Concluded that:
▫ Code needs to be parallelizable
▫ Speed up is bound, giving diminishing returns for more
processors
• Task dependent
▫ Servers gain by maintaining multiple connections on
multiple processors
▫ Databases can be split into parallel tasks
Amdahl’s Law Formula
• It deals with the potential speedup of a program using multiple
processors compared to a single processor.
• For program running on single processor
— Fraction f of code infinitely parallelizable with no scheduling overhead
— Fraction (1-f ) of code inherently serial
— T is total execution time for program on single processor
— N is number of processors that fully exploit parallel portions of code
• Conclusions
▫ When f is small, the use of parallel processors has little effect.
▫ N ->∞, speedup is bound by 1/(1 – f)
 So, diminishing returns for using more processors
References
• AMDA67 Amdahl, G. “Validity of the SingleProcessor Approach to Achieving Large-Scale
Computing Capability”, Proceedings of the AFIPS
Conference, 1967.