7. Instruction Encoding

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Recap

• Technology trends
• Cost/performance

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Measuring and Reporting Performance

• What does it mean to say computer X is faster
  than computer Y?

• E.g. Machine A executes a program in 10s Machine
  B executes
• the same program in 15s.
• Which is true
• A is 50 faster than B?
• A is 33 faster than B?

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Performance

• HPs definition X is n times faster than Y
  means

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Example

• E.g. Machine A executes a program in 10s Machine
  B executes
• the same program in 15s.
• Which is true
• A is 50 faster than B?
• A is 33 faster than B?

• Answer 1) A is 50 faster than B

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Performance

• Response time?
• Throughput?

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Measuring Performance

• Focus on execution time of real programs

• Measuring execution time?
• Wall clock time (elapsed time)
• CPU time (excludes I/O and other processes)
• User CPU time
• System CPU time

iota time gcc -g tmpcnv.s -o tmpcnv real
0m3.352s user 0m0.367s sys 0m0.468s
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Choosing Programs to Measure Performance

• Real Programs
• Compilers, text-processing, CAD tools, etc.
• Modified applications
• Scripted or modified for portability
• Kernels
• Attempt to extract key sections from real
  programs (Livermore loops, Linpack)
• Toy Benchmarks
• Short examples (e.g. Sieve of Eratosthenes)
• Synthetic Benchmarks
• Whetstone, Dhrystone

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Benchmarking

• HP car magazines are more scientific about
  reporting performance than many CS journals!

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Benchmark Suites

• Collections of benchmarks
• E.g. SPEC CPU2000 (INT and FP)
• 25 real FORTRAN/C/C programs, modified for
  portability
• Specific graphics benchmarks

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Server Benchmarks

• SPEC also has server benchmarks
• File server
• Web server
• TPC Transaction Processing Council
• Various transaction processing benchmarks

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Embedded Benchmarks

• Much less well developed
• Tend to use Dhrystone!
• EEMBC
• Recent development
• 34 benchmarks (mainly kernels) in five
  application areas

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Summarising Performance Measurements

• Complex area
• Weighted arithmetic mean
• Geometric mean
• Normalised results

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1.6 Quantitative Principles

• Make the common case fast!
• E.g. addition focus on normal addition, not
  overflow situations

• Amdahls Law
• Quantifies improvements gained by focussing on
  one aspect of a design

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Amdahls Law
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Example

• We are considering an enhancement that is 10
  times faster than the original, but is only used
  40 of the time.

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CPU Performance

• CPU time related to clock speed
• Period (e.g. 1ns)
• Rate (e.g. 1GHz)
• Also interested in Cycles Per Instruction (CPI)

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Three Equal Factors

• Clock rate (technology)
• CPI (architecture)
• Instruction count (architecture and compiler)

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Measuring IC CPI

• Many modern processors include hardware counters
  for instructions and clock cycles
• Simulations can give even more detail
• Time consuming, but can be very accurate

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Another Principle Locality

• Locality of Reference
• 90/10 Rule
• Also applies to data
• Two aspects
• Temporal locality
• Spatial locality

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Taking Advantage of Parallelism

• Key principle for improving performance
• Examples
• System level parallel processing, disk arrays,
  etc.
• Processor level pipelining
• Digital design caches, ALU adders, etc.

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1.7 Putting It All Together Performance
Price/Performance

• Measure performance and performance/cost for
  three categories
• Desktop (SPEC INT and FP)
• TP Servers (TPC-C)
• Embedded Processors (EEMBC)

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Desktop

• Integer
• Performance/cost tracks performance
• FP
• Not as closely related
• Pentium 4 much better than Pentium III
• AMD Athlon very good value for money

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Servers

• Twelve systems
• Six top performers
• Six best price-performance
• Multiprocessors
• 3 P3s 280 P3s
• Cost
• 131,000 15 million

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Embedded Processors

• Difficult to assess
• Benchmarks very new
• Designs very application-specific
• Power a major constraint
• Cost difficult to quantify (are support chips
  required?)

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Embedded Processors

• Range
• 500MHz AMD K6 (78) and IBM PowerPC (94) used
  for network switches, etc.
• 167MHz NEC VR 5432 (25) popular in colour laser
  printers
• 180MHz NEC VR 4122 (33) popular in PDAs (low
  power)

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1.8 Another View Power Consumption and
Efficiency

• Embedded processors from previous example power
  ranged from 700mW to 9600mW
• Fig. 1.27 Performance/watt
• NEC VR 4122 huge leader

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1.9 Fallacies and Pitfalls

• Fallacy Relative performance of two similar
  processors can be judged by clock rate or by a
  single benchmark
• Factors such as pipeline structure and memory
  system have major impact
• E.g. Pentium III vs. Pentium 4 (Fig. 1.28)

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1.7GHz P4 vs 1.0GHz P3
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Fallacies and Pitfalls

• Fallacy Benchmarks remain valid indefinitely
• Optimisations change
• Perhaps deliberately!
• Even real programs are affected by changes in
  technology
• E.g. gcc increasing percentage is system time
• SPEC has adapted considerably

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Fallacies and Pitfalls

• Pitfall Comparing hand-coded assembly and
  compiled high-level language performance
• E.g. embedded processor benchmarks
• Hand-coded is 5 87 times faster!

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