1. Benchmarks Programs specifically chosen to measure performance
Must reflect typical workload of the user
Benchmark types
Real applications
Small benchmarks
Benchmark suites
Synthetic benchmarks

2. Real Applications
Workload: Set of programs a typical user runs day in and day out.
To use these real applications for metrics is a direct way of comparing the execution time of the workload on two machines.
Using real applications for metrics has certain restrictions:
They are usually big
Takes time to port to different machines
Takes considerable time to execute
Hard to observe the outcome of a certain improvement technique

3. Comparing & Summarizing Performance
Computer A
Computer B
Program 1
1 s
100 s
Program 2
1000 s
Total time
1001 s
200 s
A is 100 times faster than B for program 1
B is 10 times faster than A for program 2
For total performance, arithmetic mean is used:

4. Arithmetic Mean
If each program, in the workload, are not run equal # times, then we have to use weighted arithmetic mean:
Suppose that the program 1 runs 10 times as often as the program 2. Which machine is faster?
weight
Computer A
Computer B
Program 1 (seconds) 10 1
100
Program 2 (seconds)
1000
Weighted AM - ?

5. Small Benchmarks
Small code segments which are common in many applications
For example, loops with certain instruction mix
for (j = 0; j<8; j++) S = S + Aj  Bi-j
Good for architects and designers
Since small code segments are easy to compile and simulate even by hand, designers use these kind of benchmarks while working on a novel machine
Can be abused by compiler designers by introducing special-purpose optimizations targeted at specific benchmark.

6. Benchmark Suites SPEC (Standard Performance Evaluation Corporation)
Non-profit organization that aims to produce "fair, impartial and meaningful benchmarks for computers”
Began in SPEC89 (CPU intensive)
Companies agreed on a set of real programs and inputs which they hope reflect a typical user’s workload best.
Valuable indicator of performance
Can still be abused
Updates are required as the applications and their workload change by time

7. SPEC Benchmark Sets CPU Performance (SPEC CPU2006)
Graphics (SPECviewperf)
High-performance computing (HPC2002, MPI2007, OMP2001)
Java server applications (jAppServer2004)
a multi-tier benchmark for measuring the performance of Java 2 Enterprise Edition (J2EE) technology-based application servers.
Mail systems (MAIL2001, SPECimap2003)
Network File systems (SFS97_R1 (3.0))
Web servers (SPEC WEB99, SPEC WEB99 SSL)
More information:

8. SPECInt Integer Benchmarks Name Description 400.perlbench
Programming Language
401.bzip2
Compression
403.gcc
C Compiler
429.mcf
Combinatorial Optimization
445.gobmk
Artificial Intelligence
456.hmmer
Search Gene Sequence
458.sjeng
462.libquantum
Physics / Quantum Computing
464.h264ref
Video Compression
471.omnetpp
Discrete Event Simulation
473.astar
Path-finding Algorithms
483.xalancbmk
XML Processing

9. SPECfp Floating Point Benchmarks Name Type wupwise
Quantum chromodynamics
swim
Shallow water model
mgrid
multigrid solver in 3D potential field
applu
Parabolic/elliptic partial dif. equation
mesa
Three-dimensional graphics library
galgel
Computational fluid dynamics
art
Image recognition using neural nets
equake
Seismic wave propagation simulation
facerec
Image recognition of faces
ammp
Computational chemistry
lucas
Primality testing
fma3d
Crash simulation
sixtrack
High-energy nuclear physics acceleration design
apsi
meteorology; pollutant distribution

10. SPEC CPU2006 – Summarizing
SPEC ratio: the execution time measurements are normalized by dividing the measured execution time by the execution time on a reference machine
Sun Microsystems Fire V20z, which has an AMD Opteron 252 CPU, running at 2600 MHz.
164.gzip benchmark executes in 90.4 s.
The reference time for this benchmark is 1400 s,
benchmark is 1400/90.4 × 100 = 1548 (a unitless value)
Performances of different programs in the suites are summarized using “geometric mean” of SPEC ratios.

11. Pentium III & Pentium 4

12. Comparing Pentium III and Pentium 4
Ratio
Pentium III
Pentium 4
CINT2000/Clock rate in MHz
0.47
0.36
CFP2000/Clock rate in MHz
0.34
0.39
Implementation efficiency?

13. SPEC WEB99 System Processor # of disk drivers # of CPUs # of networks
Clock
rate
(GHz)
Result
1550/1000
Pentium III 2 1
2765
1650 3
1.4
1810
2500 8 4
1.13
3435
2550
1.26
1454
2650
Pentium 4 Xeon 5
3.06
5698
4600 10
2.2
4615
6400/700
Pentium III Xeon
0.7
4200
6600
Pentium 4 Xeon MP
6700
8450/700 7
8001

14. Power Consumption Concerns
Performance studied at different levels:
Maximum power
Intermediate level that conserves battery life
Minimum power that maximizes battery life
Intel Mobile Pentium & Pentium M: two available clock rates
Maximum
Reduced clock rate
Pentium 1.6/0.6 GHz
Pentium 2.4/1.2 GHz
Pentium 1.2/0.8 GHz

15. Three Intel Mobile Processors

16. Energy Efficiency

17. Synthetic Benchmarks
Artificial programs constructed to try to match the characteristics of a large set of program.
Goal: Create a single benchmark program where the execution frequency of instructions in the benchmark simulates the instruction frequency in a large set of benchmarks.
Examples:
Dhrystone, Whetstone
They are not real programs
Compiler and hardware optimizations can inflate the improvement far beyond what the same optimization would do with real programs

18. Amdahl’s Law in Computing
Improving one aspect of a machine by a factor of n does not improve the overall performance by the same amount.
Speedup = (Performance after imp.) / (Performance before imp.)
Speedup = (Execution time before imp.)/ (Execution time after imp.)
Execution Time After Improvement = Execution Time Unaffected + (Execution Time Affected/n)

19. Amdahl’s Law
Example: Suppose a program runs in 100 s on a machine, with multiplication responsible for 80 s of this time.
How much do we have to improve the speed of multiplication if we want the program to run 4 times faster?
Can we improve the performance by a factor 5?

20. Amdahl’s Law
The performance enhancement possible due to a given improvement is limited by the amount that the improved feature is used.
In previous example, it makes sense to improve multiplication since it takes 80% of all execution time.
But after certain improvement is done, the further effort to optimize the multiplication more will yield insignificant improvement.
Law of Diminishing Returns
A corollary to Amdahl’s Law is to make a common case faster.

21. Examples
Suppose we enhance a machine making all floating-point instructions run five times faster. If the execution time of some benchmark before the floating-point enhancement is 10 seconds, what will the speedup be if half of the 10 seconds is spent executing floating-point instructions?
We are looking for a benchmark to show off the new floating-point unit described above, and want the overall benchmark to show a speedup of 3. One benchmark we are considering runs for 90 seconds with the old floating-point hardware. How much of the execution time would floating- point instructions have to account for in this program in order to yield our desired speedup on this benchmark?

22. Remember Total execution time is a consistent summary of performance
Execution Time = (IC  CPI)/f
For a given architecture, performance increases come from:
increases in clock rate (without too much adverse CPI effects)
improvements in processor organization that lower CPI
compiler enhancements that lower CPI and/or IC