CIS775: Computer Architecture

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CIS775 Computer Architecture

• Chapter 1 Fundamentals of Computer Design

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Course Objectives

• To evaluate the issues involved in choosing and
  designing instruction set.
• To learn concepts behind advanced pipelining
  techniques.
• To understand the hitting the memory wall
  problem and the current state-of-art in memory
  system design.
• To understand the qualitative and quantitative
  tradeoffs in the design of modern computer
  systems

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What is Computer Architecture?

• Functional operation of the individual HW units
  within a computer system, and the flow of
  information and control among them.

Programming
Parallelism
Technology
Language Interface
Computer Architecture
Interface Design (ISA)
Hardware Organization
OS
Applications
Measurement Evaluation
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Computer Architecture Topics
Input/Output and Storage
Disks, WORM, Tape
RAID
Emerging Technologies Interleaving Memories
DRAM
Coherence, Bandwidth, Latency
Memory Hierarchy
L2 Cache
L1 Cache
Addressing, Protection, Exception Handling
VLSI
Instruction Set Architecture
Pipelining, Hazard Resolution, Superscalar,
Reordering, Prediction, Speculation, Vector, DSP
Pipelining and Instruction Level Parallelism
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Computer Architecture Topics
Shared Memory, Message Passing, Data Parallelism
M
P
M
P
M
P
M
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Network Interfaces
S
Interconnection Network
Processor-Memory-Switch
Topologies, Routing, Bandwidth, Latency, Reliabili
ty
Multiprocessors Networks and Interconnections
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Measurement and Evaluation

• Architecture is an iterative process
• Searching the space of possible designs
• At all levels of computer systems

Creativity
Cost / Performance Analysis
Good Ideas
Mediocre Ideas
Bad Ideas
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Issues for a Computer Designer

• Functional Requirements Analysis (Target)
• Scientific Computing HiPerf floating pt.
• Business transactional support/decimal arith.
• General Purpose balanced performance for a range
  of tasks
• Level of software compatibility
• PL level
• Flexible, Need new compiler, portability an issue
• Binary level (x86 architecture)
• Little flexibility, Portability requirements
  minimal
• OS requirements
• Address space issues, memory management,
  protection
• Conformance to Standards
• Languages, OS, Networks, I/O, IEEE floating pt.

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Computer Systems Technology Trends

• 1988
• Supercomputers
• Massively Parallel Processors
• Mini-supercomputers
• Minicomputers
• Workstations
• PCs

• 2002
• Powerful PCs and SMP Workstations
• Network of SMP Workstations
• Mainframes
• Supercomputers
• Embedded Computers

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Why Such Change in 10 years?

• Performance
• Technology Advances
• CMOS (complementary metal oxide semiconductor)
  VLSI dominates older technologies like TTL
  (transistor transistor logic) in cost AND
  performance
• Computer architecture advances improves low-end
• RISC, pipelining, superscalar, RAID,
• Price Lower costs due to
• Simpler development
• CMOS VLSI smaller systems, fewer components
• Higher volumes
• Lower margins by class of computer, due to fewer
  services
• Function Rise of networking/local
  interconnection technology

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Growth in Microprocessor Performance
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Six Generations of DRAMs
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Updated Technology Trends(Summary)
Capacity Speed (latency) Logic 4x in 4
years 2x in 3 years DRAM 4x in 3 years 2x in
10 years Disk 4x in 2 years 2x in 10
years Network (bandwidth) 10x in 5 years

• Updates during your study period??
• BS (4 yrs)
• MS (2 yrs)
• PhD (5 yrs)

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Performance Trends(Summary)

• Workstation performance (measured in Spec Marks)
  improves roughly 50 per year (2X every 18
  months)
• Improvement in cost performance estimated at 70
  per year

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Computer Engineering Methodology
Evaluate Existing Systems for Bottlenecks
Implementation Complexity
Benchmarks
Technology Trends
Implement Next Generation System
Simulate New Designs and Organizations
Workloads
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How to Quantify Performance?
Plane
Boeing 747
BAD/Sud Concodre

• Time to run the task (ExTime)
• Execution time, response time, latency
• Tasks per day, hour, week, sec, ns
  (Performance)
• Throughput, bandwidth

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The Bottom Line Performance and Cost or Cost
and Performance?

• "X is n times faster than Y" means
• ExTime(Y) Performance(X)
• --------- ---------------
• ExTime(X) Performance(Y)
• Speed of Concorde vs. Boeing 747
• Throughput of Boeing 747 vs. Concorde
• Cost is also an important parameter in the
  equation which is why concordes are being put to
  pasture!

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Measurement Tools

• Benchmarks, Traces, Mixes
• Hardware Cost, delay, area, power estimation
• Simulation (many levels)
• ISA, RT, Gate, Circuit
• Queuing Theory
• Rules of Thumb
• Fundamental Laws/Principles
• Understanding the limitations of any measurement
  tool is crucial.

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Metrics of Performance
Application
Answers per month Operations per second
Programming Language
Compiler
(millions) of Instructions per second
MIPS (millions) of (FP) operations per second
MFLOP/s
ISA
Datapath
Megabytes per second
Control
Function Units
Cycles per second (clock rate)
Transistors
Wires
Pins
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Cases of Benchmark Engineering

• The motivation is to tune the system to the
  benchmark to achieve peak performance.
• At the architecture level
• Specialized instructions
• At the compiler level (compiler flags)
• Blocking in Spec89 ? factor of 9 speedup
• Incorrect compiler optimizations/reordering.
• Would work fine on benchmark but not on other
  programs
• I/O level
• Spec92 spreadsheet program (sp)
• Companies noticed that the produced output was
  always out put to a file (so they stored the
  results in a memory buffer) and then expunged at
  the end (which was not measured).
• One company eliminated the I/O all together.

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After putting in a blazing performance on the
benchmark test, Sun issued a glowing press
release claiming that it had outperformed Windows
NT systems on the test. Pendragon president Ivan
Phillips cried foul, saying the results weren't
representative of real-world Java performance and
that Sun had gone so far as to duplicate the
test's code within Sun's Just-In-Time compiler.
That's cheating, says Phillips, who claims that
benchmark tests and real-world applications
aren't the same thing. Did Sun issue a denial or
a mea culpa? Initially, Sun neither denied
optimizing for the benchmark test nor apologized
for it. "If the test results are not
representative of real-world Java applications,
then that's a problem with the benchmark," Sun's
Brian Croll said. After taking a beating in the
press, though, Sun retreated and issued an
apology for the optimization.Excerpted from PC
Online 1997
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Issues with Benchmark Engineering

• Motivated by the bottom dollar, good performance
  on classic suites ? more customers, better sales.
• Benchmark Engineering ? Limits the longevity of
  benchmark suites
• Technology and Applications? Limits the longevity
  of benchmark suites.

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SPEC System Performance Evaluation Cooperative

• First Round 1989
• 10 programs yielding a single number
  (SPECmarks)
• Second Round 1992
• SPECInt92 (6 integer programs) and SPECfp92 (14
  floating point programs)
• Compiler Flags unlimited. March 93
• new set of programs SPECint95 (8 integer
  programs) and SPECfp95 (10 floating point)
• benchmarks useful for 3 years
• Single flag setting for all programs
  SPECint_base95, SPECfp_base95
• SPEC CPU2000 (11 integer benchmarks CINT2000,
  and 14 floating-point benchmarks CFP2000

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SPEC 2000 (CINT 2000)Results
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SPEC 2000 (CFP 2000)Results
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Reporting Performance Results

• Reproducability
• ? Apply them on publicly available benchmarks.
  Pecking/Picking order
• Real Programs
• Real Kernels
• Toy Benchmarks
• Synthetic Benchmarks

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How to Summarize Performance

• Arithmetic mean (weighted arithmetic mean) tracks
  execution time sum(Ti)/n or sum(WiTi)
• Harmonic mean (weighted harmonic mean) of rates
  (e.g., MFLOPS) tracks execution time
  n/sum(1/Ri) or 1/sum(Wi/Ri)
• Normalized execution time is handy for scaling
  performance (e.g., X times faster than
  SPARCstation 10)
• But do not take the arithmetic mean of normalized
  execution time, use the geometric mean
  (Product(Ri)1/n)

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Performance Evaluation

• For better or worse, benchmarks shape a field
• Good products created when have
• Good benchmarks
• Good ways to summarize performance
• Given sales is a function in part of performance
  relative to competition, investment in improving
  product as reported by performance summary
• If benchmarks/summary inadequate, then choose
  between improving product for real programs vs.
  improving product to get more salesSales almost
  always wins!
• Execution time is the measure of computer
  performance!

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Simulations

• When are simulations useful?
• What are its limitations, I.e. what real world
  phenomenon does it not account for?
• The larger the simulation trace, the less
  tractable the post-processing analysis.

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Queueing Theory

• What are the distributions of arrival rates and
  values for other parameters?
• Are they realistic?
• What happens when the parameters or distributions
  are changed?

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Quantitative Principles of Computer Design

• Make the Common Case Fast
• Amdahls Law
• CPU Performance Equation
• Clock cycle time
• CPI
• Instruction Count
• Principles of Locality
• Take advantage of Parallelism

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Amdahls Law
ExTimenew ExTimeold x (1 - Fractionenhanced)
Fractionenhanced
Speedupenhanced
1
ExTimeold ExTimenew
Speedupoverall

(1 - Fractionenhanced) Fractionenhanced
Speedupenhanced
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Amdahls Law

• Floating point instructions improved to run 2X
  but only 10 of actual instructions are FP

ExTimenew
Speedupoverall

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CPU Performance Equation

• Inst Count CPI Clock Rate
• Program X
• Compiler X (X)
• Inst. Set. X X
• Organization X X
• Technology X

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Cycles Per Instruction
Average Cycles per Instruction
CPI (CPU Time Clock Rate) / Instruction Count
Cycles / Instruction Count
n
CPU time CycleTime CPI I
i
i
i 1
Instruction Frequency
n

CPI CPI F where F
I
i
i
i
i
i 1
Instruction Count

• Invest Resources where time is Spent!

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Example Calculating CPI
Base Machine (Reg / Reg) Op Freq Cycles CPI(i) (
Time) ALU 50 1 .5 (33) Load 20 2
.4 (27) Store 10 2 .2 (13) Branch 20 2
.4 (27) 1.5
Typical Mix
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Chapter Summary, 1

• Designing to Last through Trends
• Capacity Speed
• Logic 2x in 3 years 2x in 3 years
• DRAM 4x in 3 years 2x in 10 years
• Disk 4x in 3 years 2x in 10 years
• 6yrs to graduate gt 16X CPU speed, DRAM/Disk size
• Time to run the task
• Execution time, response time, latency
• Tasks per day, hour, week, sec, ns,
• Throughput, bandwidth
• X is n times faster than Y means
• ExTime(Y) Performance(X)
• --------- --------------
• ExTime(X) Performance(Y)

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Chapter Summary, 2

• Amdahls Law
• CPI Law
• Execution time is the REAL measure of computer
  performance!
• Good products created when have
• Good benchmarks, good ways to summarize
  performance
• Die Cost goes roughly with die area4

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Food for thought

• Two companies reports results on two benchmarks
  one on a Fortran benchmark suite and the other on
  a C benchmark suite.
• Company As product outperforms Company Bs on
  the Fortran suite, the reverse holds true for the
  C suite. Assume the performance differences are
  similar in both cases.
• Do you have enough information to compare the two
  products. What information will you need?

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Food for Thought II

• In the CISC vs. RISC debate a key argument of the
  RISC movement was that because of its
  simplicity, RISC would always remain ahead.
• If there were enough transistors to implement a
  CISC on chip, then those same transistors could
  implement a pipelined RISC
• If there was enough to allow for a pipelined CISC
  there would be enough to have an on-chip cache
  for RISC. And so on.
• After 20 years of this debate what do you think?
• Hint Think of commercial PCs, Moores law and
  some of the data in the first chapter of the book
  (and on these slides)

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Amdahls Law (answer)

• Floating point instructions improved to run 2X
  but only 10 of actual instructions are FP

ExTimenew ExTimeold x (0.9 .1/2) 0.95 x
ExTimeold
1
Speedupoverall


1.053
0.95