Acronym Definition
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OBMK Online Benzyl Methyl Keton
OBMK Of Blessed Memory Kill
OBMK Office of Budget Management (Ohio) Kit
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OBMK Oil-Based Muds (oil well drilling) Keeper
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OBMK Optimized Bandwidth Management (Cisco) Keeper
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OBMK Ordnance Bench Mark
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OBMK Online BenchMark
Benchmark may refer to:
Benchmark (surveying), a point of reference for a measurement
Benchmark (crude oil), a reference for and discussion of cost and/or pricing of
petroleum, such as Brent Crude and West Texas Intermediate in terms of
benchmarks based on classification differences.
Benchmark (computing), the result of running a computer program, or a set of
programs, in order to assess the relative performance of an object by running a
number of standard tests and trials against it
Benchmarking (geolocating), a sport similar to geocaching in which participants
individually go out and find benchmarks
Benchmarking, the process used in management in which organizations evaluate
various aspects of their processes in relation to the best practice, usually
within their own sector
Benchmark Capital, a venture capital firm behind various startups, such as (and
including) eBay.
The term benchmark originates from the chiseled horizontal marks that surveyors
made, into which an angle-iron could be placed to bracket ("bench") a levelling
rod, thus ensuring that the levelling rod can be repositioned in exactly the
same place in the future.
In computing, a benchmark is the act of running a computer program, a set of
programs, or other operations, in order to assess the relative performance of an
object, normally by running a number of standard tests and trials against it.
The term, benchmark, is also commonly used for specially-designed benchmarking
programs themselves. Benchmarking is usually associated with assessing
performance characteristics of computer hardware, for example, the floating
point operation performance of a CPU, but there are circumstances when the
technique is also applicable to software. Software benchmarks are, for example,
run against compilers or database management systems.
Benchmarks provide a method of comparing the performance of various subsystems
across different chip/system architectures. Benchmarking is helpful in
understanding how the database manager responds under varying conditions. You
can create scenarios that test deadlock handling, utility performance, different
methods of loading data, transaction rate characteristics as more users are
added, and even the effect on the application of using a new release of the
product.
Purpose
As computer architecture advanced, it became more and more difficult to compare
the performance of various computer systems simply by looking at their
specifications. Therefore, tests were developed that could be performed on
different systems, allowing the results from these tests to be compared across
different architectures. For example, while Intel Pentium 4 processors generally
operate at a higher clock frequency than AMD Athlon XP processors, this does not
necessarily translate to more computational power. In other words a 'slower' AMD
processor, with regard to clock frequency, can perform as well on benchmark
tests as an Intel processor operating at a higher frequency.
Benchmarks are designed to mimic a particular type of workload on a component or
system. "Synthetic" benchmarks do this by specially-created programs that impose
the workload on the component. "Application" benchmarks, instead, run actual
real-world programs on the system. Whilst application benchmarks usually give a
much better measure of real-world performance on a given system, synthetic
benchmarks still have their use for testing out individual components, like a
hard disk or networking device.
Benchmarks are particularly important in semiconductor microprocessor design,
giving processor architects the ability to measure and make tradeoffs in
microarchitectural decisions. For example, if a benchmark extracts the key
algorithms of an application, it will contain the performance-sensitive aspects
of that application. Running this much smaller "snippet" on a cycle-accurate
simulator, can give clues on how to improve performance.
Prior to 2000, computer and microprocessor architects used SPEC to do this,
although SPEC's Unix-based benchmarks were quite lengthy and thus unwieldy to
use intact.
Computer manufacturers have a long history of trying to set up their systems to
give unrealistically high performance on benchmark tests that is not replicated
in real usage. For instance, during the 1980s some compilers could detect a
specific mathematical operation used in a well-known floating-point benchmark
and replace the operation with a mathematically-equivalent operation that was
much faster. However, such a transformation was rarely useful outside the
benchmark until the mid-1990s, when RISC and VLIW architectures emphasized the
importance of compiler technology as it related to performance. Benchmarks are
now regularly used by compiler companies to improve not only their own benchmark
scores, but real application performance.
Manufacturers commonly report only those benchmarks (or aspects of benchmarks)
that show their products in the best light. They also have been known to mis-represent
the significance of benchmarks, again to show their products in the best
possible light. Taken together, these practices are called bench-marketing.
Users are recommended to take benchmarks, particularly those provided by
manufacturers themselves, with ample quantities of salt unless the benchmarks
are certified and relate directly to a recognizable application workload.
Ideally benchmarks should only substitute for real applications if the
application is unavailable, or too difficult or costly to port, to a specific
processor or computer system. If performance is really critical, the only
benchmark that matters is the actual workload that the system is to be used for.
If that is not possible, benchmarks that resemble real workloads as closely as
possible should be used, and even then used with skepticism unless independently
certified. It is quite possible for system A to outperform system B when running
a certain program on the workload in the benchmark, and the order to be reversed
with the same program on a real life workload.
Challenges
Benchmarking is not easy and often involves several iterative rounds in order to
arrive at predictable, useful conclusions. Interpretation of benchmarking data
is also extraordinarily difficult. Here is a partial list of common challenges:
Vendors tend to tune their products specifically for industry-standard
benchmarks. Norton SysInfo (SI) is particularly easy to tune for, since it
mainly biased toward the speed of multiple operations. Use extreme caution in
interpreting such results.
Benchmarks generally do not give any credit for any qualities of service aside
from raw performance. Examples of unmeasured qualities of service include
security, availability, reliability, execution integrity, serviceability,
scalability (especially the ability to quickly and nondisruptively add or
reallocate capacity), etc. There are often real trade-offs between and among
these qualities of service, and all are important in business computing. TPC
Benchmark specifications partially address these concerns by specifying ACID
property tests, database scalability rules, and service level requirements.
In general, benchmarks do not measure TCO. TPC Benchmark specifications
partially address this concern by specifying that a price/performance metric
must be reported in addition to a raw performance metric, using a simplified TCO
formula.
Benchmarks seldom measure real world performance of mixed workloads — running
multiple applications concurrently in a full, multi-department/multi-application
business context. For example, IBM's mainframe servers (System z9) excel at
mixed workload, but industry-standard benchmarks don't tend to measure the
strong I/O and large/fast memory design such servers require. (Most other server
architectures dictate fixed function/single purpose deployments, e.g. "database
servers" and "Web application servers" and "file servers," and measure only
that. The better question is, "What more computing infrastructure would I need
to fully support all this extra workload?")
Vendor benchmarks tend to ignore requirements for development, test, and
disaster recovery computing capacity. Vendors only like to report what might be
narrowly required for production capacity in order to make their initial
acquisition price seem as low as possible.
Benchmarks are having trouble adapting to widely distributed servers,
particularly those with extra sensitivity to network topologies. The emergence
of grid computing, in particular, complicates benchmarking since some workloads
are "grid friendly," while others are not.
Users can have very different perceptions of performance than benchmarks may
suggest. In particular, users appreciate predictability — servers that always
meet or exceed SLAs. Benchmarks tend to emphasize mean scores (IT perspective)
rather than low standard deviations (user perspective).
Many server architectures degrade dramatically at high (near 100%) levels of
usage — "fall off a cliff" — and benchmarks should (but often do not) take that
factor into account. Vendors, in particular, tend to publish server benchmarks
at continuous ~80% usage — a totally unreal situation — and do not document what
happens to the overall system when/if demand spikes beyond that level.
Benchmarking institutions often disregard or do not follow basic scientific
method. This includes, but is not limited to: small sample size, lack of
variable control, and the limited repeatability of results. [1]
Types of benchmarks
Real program
word processing software
tool software of CDA
user's application software (MIS)
Kernel
contains key codes
normally abstracted from actual program
popular kernel: Livermore loop
linpack benchmark (contains basic linear algebra subroutine written in FORTRAN
language)
results are represented in MFLOPS
Toy Benchmark/ micro-benchmark
user can program it and use it to test computer's basic components
automatic detection of computer's hardware parameters like number of registers,
cache size, memory latency
Synthetic Benchmark
Procedure for programming synthetic Bench mark
take statistics of all type of operations from plenty of application programs
get proportion of each operation
write a program based on the proportion above
Types of Synthetic Benchmark are:
Whetstone
Dhrystone
Its results are represented in KWIPS (kilo whetstone instructions per second).
It is not suitable for measuring pipeline computers.
I/O benchmarks
Parallel benchmarks: used on machines with multiple processors or systems
consisting of multiple machines.
Common benchmarks
Industry Standard (audited and verifiable)
Standard Performance Evaluation Corporation (SPEC)
Transaction Processing Performance Council (TPC)
BAPCoan industry consortium developing benchmarks for Windows personal computers
Synchromesh Computing benchmark tests
The Embedded Microprocessor Benchmark Consortium (EEMBC)
Others
Khornerstone
Aquamark
GL Excess
The BRL-CAD Benchmark
Open source benchmarks
miniBench: a comprehensive commandline benchmark written in C++. miniBench is
intended to be cross-platform and contains over 90 different tests. miniBench is
a branch of OpenSourceMark.
TPoX: An XML transaction processing benchmark for XML databases
Dhrystone: integer arithmetic performance
Fhourstones: an integer benchmark
Whetstone: floating-point arithmetic performance
ApFloat: floating point
Linpack / LAPACK
OpenSourceMark: A powerful, comprehensive set of open source system benchmarks
and utilities written primarily in Delphi. OpenSourceMark has a user friendly
GUI and features a flexible result viewer.
GliBench: a Gui based benchmarking tool to check CPU and hard disk performance.
MemPerf: memory bandwidth
LLCBench: a group of benchmark for cache, MPI,etc.
LMbench: a suite of simple, portable benchmarks for OS and some CPU / Memory
parameters
Calibrator: a small cache-memory and TLB Calibration Tool written in C. Results
include cache size,linesize, access/miss latency, TLB entries, pagesize, miss
penalty, memory access latency. gnuplot scripts are also generated to display
results graphically.
X-RayAutomatic Measurement of Memory Hierarchy Parameters
nbench: Memory, integer and floating point comparison with AMD K6 233MHz ported
from BYTE Magazine's BYTEmark benchmark program.
Ubench: Unix Benchmark Utility for testing CPU(s) and memory.
NAS parallel benchmarks
PAL: A benchmark for realtime physics engines
Povray: 3D render
SPLASH:Stanford Parallel Applications for Shared Memory (SPLASH)
Iometer: I/O subsystem measurement and characterization tool for single and
clustered systems.
Iozone file I/O a filesystem benchmark tool. The benchmark generates and
measures a variety of file operations.
Bonnie++: File I/O
netperf : network throughput and latency benchmark
GENESIS distributed memory benchmark suite
HINT: It ranks a computer system as a whole.
Himeno Benchmark
STREAM : measures sustainable memory bandwidth the corresponding computation
rate for simple vector kernels.
SKaMPIa suite of tests designed to measure the performance of MPI.
GL O.B.S. : OpenGL Open Benchmark Suite.
MediaBench : Benchmark suite for multimedia systems.
VMmark, a server virtualization benchmark suite from VMware.
Microsoft Windows benchmarks
OpenSourceMark: A powerful, comprehensive set of open source system benchmarks
and utilities written primarily in Delphi. OpenSourceMark has a user friendly
GUI and features a flexible result viewer.
miniBench: a comprehensive commandline benchmark written in C++. miniBench is
intended to be cross-platform and contains over 90 different tests. miniBench is
a branch of OpenSourceMark.
PassMark Software: PerformanceTest (32-bit or 64-bit)
Lavalys EVEREST
SiSoftware Sandra
Futuremark:3DMark, PCMark, SPMark
BAPCo: Mobilemark, SYSmark, Webmark
BYTEmark benchmark suite
REALiX HWiFO32
DocMemory Diagnostic software
CD Speed 99
CPUmark
CPU-Z
InfoTool
WinBench 99
CPU Rightmark
Whetstone
PiFast
Super PI
Maxon:Cinebench
Primate Labs:Geekbench
Mac OS X benchmarks
Spiny:Xbench
Maxon:Cinebench
Primate Labs:Geekbench
Java benchmarks
JatMark Performance Benchmark
Embedded Systems Benchmarks
The following are benchmarks published by the EEMBC specifically for embedded
systems and consumer devices [2].
AutoBench
ConsumerBench
DENBench
GrinderBench (Java)
Networking
OABench
StorageBench
TeleBench
Books
Jim Gray (Editor), The Benchmark Handbook for Database and Transaction Systems
(2nd Edition), Morgan Kaufmann, 1993, ISBN 1-55860-292-5
Database Benchmarking Practical Methods for Oracle & SQL Server Dr. Bert Scalzo,
Kevin Kline, Claudia Fernandez, Donald K. Burleson, Mike Ault, 2007, ISBN
0-9776715-3-4

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