Transcript Document 7544064

Performance Analysis, Tools and
Optimization
Philip J. Mucci
Kevin S. London
University of Tennessee, Knoxville
ARL MSRC Users’ Group Meeting
September 2, 1998
PET, UT and You
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Training
Environments
Benchmarking
Evaluation and Reviews
Consulting
Development
Training
• Courses on Benchmarking, Performance
Optimization, Parallel Tools
• Provides good mechanism for technology
transfer
• Develop needs and direction from the
interaction with the user community
• Tremendous knowledge base from which to
draw
Environments
• Use of the MSRC environments provides
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Bug reports to the vendor
System tuning
System administrator support
Analysis of software needs
Performance evaluation
Researchers access to advanced hardware
Performance Understanding
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In order to optimize we must understand
Why is our code performing a certain way?
What can be done about it?
How good can we do?
Results in confidence, efficiency and better
code development
• Time spent is an investment in the future
Tool Evaluation
Ptools Consortium
• Review of available performance tools,
particularly parallel
• Regular reports are issued
• Tools that we find useful get presented to
the developers in training or consultation
• Installation, testing and training
• Example: VAMPIR for scalability analysis
Optimization Course
• Course focuses on compiler options,
available tools and single processor
performance
• Single biggest bottleneck to many codes,
especially cache performance
• Why? Link speeds have increased within an
order of magnitude of memory bandwidths
• Also, MPI and language specific issues
Benchmarks
• CacheBench - performance of the
memory hierarchy
• MPBench - performance of core MPI
operations
• BLASBench - performance of dense
numerical kernels
• Intended to provide an orthogonal set of
low-level benchmarks with which we can
parameterize codes
Cache Performance
Cache Performance
• Tuning for caches is difficult without some
understanding of computer architecture
• No way to really know what’s in the cache
during a given point in an application
• Factor of 2-4 performance increase is
common
• Develop a tool to help identify regions in
the source code, a specific reference.
Cache Simulator
• Profiling the code reveals cache problems
• Automated instrumentation of offending
routines via a GUI or by hand
• Link with simulator library
• Make architecture configuration file
• Addresses are traced and simulated
• Miss locations are recorded and reports are
generated
PerfAPI
• A standardized interface to hardware
performance counters
• Easily usable by application engineers as
well as tool developers
• Intended for
– Performance tools
– Evaluation
– Modeling
• Watch http://www.cs.utk.edu/~mucci/pdsa
High Performance Debugger
• Industry wide lack of good debugging
support for parallel programs
• TotalView is expensive and GUI only
• Bandwidth is often not-available off-site
• Based on dbx and gdb as backends
• Uses p2d2 from NASA as a framework
• Standardized, familiar command-line
interface
MPI Connect
• Connects separate MPI jobs with PVM
• 3 function calls to enroll
• Uses include
– Metacomputing with Vendor MPI
– Dynamic and Fault Tolerant MPI jobs now
The Future
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BYOC Workshops
Regular Training Schedule
Web Based Training
Consulting
Cross-MSRC Information Exchange
Technology Transfer
Tool development
Origin 2000 Performance
Prescription
• Always use dplace on all codes
• Always use
-LNO:cache_size2=4096
• For accuracy compile and link with
-O2 -IPA -SWP:=ON -LNO -TENV:X=0-5
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-Ofast=ip27 -OPT:roundoff=0-3
-OPT:IEEE_arithmetic=1-3
Origin 2000 Performance
Prescription
• In Fortran, innermost array index should
change fastest
• Use functions in
-lcomplib.sgimath or -lscs
-lfastm
-lm
• Use MPI_Ixxxx primitives
• Always execute IRECV early
Vampir Timeline Display
Vampir Global Activity Chart
Identifying a Message in Vampir
Identifying a Message in Vampir
Nupshot Display