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Chapter: Advanced Computer Architecture : Instruction Level Parallelism

Measuring and Reporting Performance

The computer user is interested in reducing response time( the time between the start and the completion of an event) also referred to as execution time.

Measuring and Reporting Performance


The computer user is interested in reducing response time( the time between the start and the completion of an event) also referred to as execution time. The manager of a large data processing center may be interested in increasing throughput( the total amount of work done in a given time).


Even execution time can be defined in different ways depending on what we count. The most straightforward definition of time is called wall-clock time, response time, or elapsed time, which is the latency to complete a task, including disk accesses, memory accesses, input/output activities, operating system overhead


Choosing Programs to Evaluate Performance


A computer user who runs the same programs day in and day out would be the perfect candidate to evaluate a new computer. To evaluate a new system the user would simply compare the execution time of her workload—the mixture of programs and operating system commands that users run on a machine.


There are five levels of programs used in such circumstances, listed below in decreasing order of accuracy of prediction.


1. Real applications— Although the buyer may not know what fraction of time is spent on these programs, she knows that some users will run them to solve real problems. Examples are compilers for C, text-processing software like Word, and other applications like Photoshop. Real applications have input, output, and options that a user can select when running the program. There is one major downside to using real applications as benchmarks: Real applications often encounter portability problems arising from dependences on the operating system or compiler. Enhancing portability often means modifying the source and sometimes eliminating some important activity, such as interactive graphics, which tends to be more system-dependent.


2.  Modified (or scripted) applications—In many cases, real applications are used as the building block for a benchmark either with modifications to the application or with a script that acts as stimulus to the application. Applications are modified for two primary reasons: to enhance portability or to focus on one particular aspect of system performance. For example, to create a CPU-oriented benchmark, I/O may be removed or restructured to minimize its impact on execution time. Scripts are used to reproduce interactive behavior, which might occur on a desktop system, or to simulate complex multiuser interaction, which occurs in a server system.


Kernels—Several attempts have been made to extract small, key pieces from real programs and use them to evaluate performance. Livermore Loops and Linpack are the best known examples. Unlike real programs, no user would run kernel programs, for they exist solely to evaluate performance. Kernels are best used to isolate performance of individual features of a machine to explain the reasons for differences in performance of real programs.


4. Toy benchmarks—Toy benchmarks are typically between 10 and 100 lines of code and produce a result the user already knows before running the toy program. Programs like Sieve of Eratosthenes, Puzzle, and Quicksort are popular because they are small, easy to type, and run on almost any computer. The best use of such programs is beginning programming assignments


5. Synthetic benchmarks—Similar in philosophy to kernels, synthetic benchmarks try to match the average frequency of operations and operands of a large set of programs. Whetstone and Dhrystone are the most popular synthetic benchmarks.


Benchmark Suites


Recently, it has become popular to put together collections of benchmarks to try to measure the performance of processors with a variety of applications. One of the most successful attempts to create standardized benchmark application suites has been the SPEC (Standard Performance Evaluation Corporation), which had its roots in the late 1980s efforts to deliver better benchmarks for workstations. Just as the computer industry has evolved over time, so has the need for different benchmark suites, and there are now SPEC benchmarks to cover different application classes, as well as other suites based on the SPEC model. Which is shown in figure

Desktop Benchmarks


Desktop benchmarks divide into two broad classes: CPU intensive benchmarks and graphics intensive benchmarks intensive CPU activity). SPEC originally created a benchmark set focusing on CPU performance (initially called SPEC89), which has evolved into its fourth generation: SPEC CPU2000, which follows SPEC95, and SPEC92.


Although SPEC CPU2000 is aimed at CPU performance, two different types of graphics benchmarks were created by SPEC: SPEC viewperf is used for benchmarking systems supporting the OpenGL graphics library, while SPECapc consists of applications that make extensive use of graphics. SPECviewperf measures the 3D rendering performance of systems running under OpenGL using a 3-D model and a series of OpenGL calls that transform the model. SPECapc consists of runs of three large applications:


1.  Pro/Engineer: a solid modeling application that does extensive 3-D rendering. The input script is a model of a photocopying machine consisting of 370,000 triangles.


SolidWorks 99: a 3-D CAD/CAM design tool running a series of five tests varying from I/O intensive to CPU intensive. The largetest input is a model of an assembly line consisting of 276,000 triangles.


3. Unigraphics V15: The benchmark is based on an aircraft model and covers a wide spectrum of Unigraphics functionality, including assembly, drafting, numeric control machining, solid modeling, and optimization. The inputs are all part of an aircraft design.


Server Benchmarks


Just as servers have multiple functions, so there are multiple types of benchmarks. The simplest benchmark is perhaps a CPU throughput oriented benchmark. SPEC CPU2000 uses the SPEC CPU benchmarks to construct a simple throughput benchmark where the processing rate of a multiprocessor can be measured by running multiple copies (usually as many as there are CPUs) of each SPEC CPU benchmark and converting the CPU time into a rate. This leads to a measurement called the SPECRate. Other than SPECRate, most server applications and benchmarks have significant I/O activity arising from either disk or network traffic, including benchmarks for file server systems, for web servers, and for database and transaction processing systems. SPEC offers both a file server benchmark (SPECSFS) and a web server benchmark (SPECWeb). SPECSFS (see http://www.spec.org/osg/sfs93/) is a benchmark for measuring NFS (Network File System) performance using a script of file server requests; it tests the performance of the I/O system (both disk and network I/O) as well as the CPU. SPECSFS is a throughput oriented benchmark but with important response time requirements.


Transaction processing benchmarks measure the ability of a system to handle transactions, which consist of database accesses and updates. All the TPC benchmarks measure performance in transactions per second. In addition, they include a response-time requirement, so that throughput performance is measured only when the response time limit is met. To model real-world systems, higher transaction rates are also associated with larger systems, both in terms of users and the data base that the transactions are applied to. Finally, the system cost for a benchmark system must also be included, allowing accurate comparisons of cost-performance.


Embedded Benchmarks


Benchmarks for embedded computing systems are in a far more nascent state than those for either desktop or server environments. In fact, many manufacturers quote Dhrystone performance, a benchmark that was criticized and given up by desktop systems more than 10 years ago! As mentioned earlier, the enormous variety in embedded applications, as well as differences in performance requirements (hard real-time, soft real-time, and overall cost-performance), make the use of a single set of benchmarks unrealistic.


In practice, many designers of embedded systems devise benchmarks that reflect their application, either as kernels or as stand-alone versions of the entire application. For those embedded applications that can be characterized well by kernel performance, the best standardized set of benchmarks appears to be a new benchmark set: the EDN Embedded Microprocessor Benchmark Consortium (or EEMBC–pronounced embassy). The EEMBC benchmarks fall into five classes: automotive/industrial, consumer, networking, office automation, and telecommunications Figure shows the five different application classes, which include 34 benchmarks.


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