This document discusses instrumentation and analysis of the NAS Parallel Benchmarks (NPB) application using the Extrae tracing library. It summarizes the tests performed on local and remote machines using 2, 4, 8, 16, and 32 processes. Key metrics like computation time, communication time, load imbalance, and bottlenecks are measured. The analysis shows the NPB application scales well on the remote server but not the local laptop beyond 16 processes due to increased communication and wait times.

1. Instrumentation and
analysis of NPB
Zafar Gilani
EMDC 2012
Measurement Tools and Techniques
UPC

2. Outline
● Introduction to benchmark app
● Testbeds
● Instrumentation
● Traces
● Measurement criterion
● Evaluation
● Anomalies
● Conclusions

3. 1
Introduction to benchmark app
● NPB = NAS Parallel Benchmarks.
● A small set of programs designed to
evaluate performance of parallel
supercomputers.
● 5 kernels, 3 pseudo applications.
● 3 versions: Serial, OpenMP, MPI.
● 8 kind of classes of tests:
○ S - small, for quick tests
○ W - workstation size
○ A, B, C - standard tests, ~4x increase from A to C
○ D, E, F - large tests, ~16x increase from A to C

4. 2
Testbeds
Local Remote
Machine type Laptop Server
Processor Intel Core i3-330M Intel Xeon E5645
2.13GHz 2.40GHz
Cores 2 6
Cache (MB) 3 12
Memory (GB) 3 24

5. 3
Instrumentation
● Preload Extrae's MPI trace library
"libmpitrace.so".
● The library intercepts all the MPI calls and
traces all the MPI events.
● Instrumented and executed:
○ NPB version 3.3 stable
○ NPB3.3-MPI
○ IS (Integer Sort) kernel with 2, 4, 8, 16 and 32 procs
● Per experiment:
○ Size of problem: Class C, 135 million values approx.
○ Iterations: 10

6. 4
Local
traces
Exec
Comm

7. 5
Remote
traces

8. Evaluation & Comparative
Analysis

9. 6
Measurement criterion
Metric Relevance to NPB-MPI Integer Sort
Computation time General idea of speed-up.
Communication time Impact of increasing number of processes
on communication.
Load imbalance Which processes or threads do less as
compared to others.
Bottlenecks Performance bottlenecks.
L1 cache misses To see how many times the CPU had to
go to other memory to find data.

10. 7
Computation time
● Measured: thread processing time.
● Local:
○ increase in time directly proportional to nprocs
○ upto 32 processes
○ poor scalability
● Remote:
○ decrease in time directly proportional to nprocs
○ upto 32 processes
○ good scalability

11. 8

12. 9
Communication time
● Overall communication time is determined
by the process taking maximum time.
● Local:
○ rapid increase in time as number of processes are
increased
● Remote:
○ nominal increase in time as number of processes
are increased

13. 10

14. 11
Load Imbalance
● On boada
○ For nprocs = 4, threads = {2, 3} are lazy.
○ For nprocs = 16, threads = {5, 6, 7, 8, 12} are lazy.
Exec
Wait
Comm

15. 12
Bottlenecks
● For nprocs = {8, 16, 32}, one or more
processes takes more time.
○ Wait/Wait All signals.
○ Typical times for local machine is around 1000 ms.
○ Typical times for remote machine is around 250 ms.
■ 4x difference (threads in remote machine have
shorter wait time).

16. 13
Wait
I/O

17. 14
L1 cache misses
● Cache misses in local machine are more
expensive: typically costing 5x more time.
○ Cache size difference? Local has to "look"
elsewhere more often.
■ i3 has 3MB cache.
■ Xeon has 12MB cache.

18. 15

19. 16
Anomalies
● For 32 threads:
○ Time taken to spawn threads varies.
○ Remote takes less time to spawn 32 threads.
○ Possible reasons:
■ Acquiring locks and switching between resource
acquisition and release is costly.
● Time taken by "other" jobs also varies:
○ But these generally vary from system to system.

20. 17
Spawning
Others ??

21. 18
Conclusions
● Instrumentation is necessary to reveal
performance insights of parallel code.
● Extrae supports a handy procedure for
automatic instrumentation.
● Some interesting observations:
○ IS does not properly scale on low-end machines
beyond 16 procs.
○ Scales nicely on a server such as boada.
○ IS code becomes communication intensive when
nprocs is increased.
○ Some bottlenecks deteriorate performance.

22. Instrumentation and
analysis of NPB
Zafar Gilani
EMDC 2012
Measurement Tools and Techniques
UPC