jueves, 24 de mayo de 2012

[DPS Class] Contributions WEEK 16

This week I work with Rafael Lopez, we look for some testing codes for the cluster, also, we help our parterns to configure their computers. We add some new nodes to the cluster.

The examples are the shown the past thursday.

  • Rafael
  • Emmanuel
  • Victor

jueves, 17 de mayo de 2012

[DPS Class] Contributions WEEK 15

This week I work with Rafael Lopez and we implements a monitoring system for the cluster Benchmarking, also, we reconfigure all the cluster from zero, and we simplify the configuration of the nodes. Also, we write some script for automate the nodes configuration.

Download the scripts: scripts_cluster.tar.gz

  • Rafael
  • Emmanuel
  • Gaby

miércoles, 9 de mayo de 2012

[DPS Class] Contributions WEEK 14

This week I did a research about Benchmarking in that research I include a very simple definitions, and a practice that I did with Linpack test

  • Rafael.
  • Cecy.
  • Alex
The references are in the page.

[DPS Class] Benchmarks

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 mostly utilized for the purposes of elaborately-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.

Wikipedia: Benchmark

Supercomputing Benchmark

The number and type of benchmark suites used to study supercomputer performance has varied widely over the years. In early studies, an ad hoc collection of programs was typically used to measure the performance of a given system relative to a known performance benchmark. Eventually, this practice evolved into groups of programs explicitly designed as supercomputer benchmark suites.

The most widely used benchmarks for performance on supercomputing clusters are: the SPEChpc96 suite; the Livermore Loops; and for scientific machines, the Linpack Kernels.

Some general examples of individual computer benchmarks:
  • Dhrystone - Integer benchmark for UNIX systems
  • Whetstone - Floating point benchmark for minicomputers
  • I/O benchmarks
  • MIPS
  • Synthetic benchmarks
  • Kernel benchmarks
  • SPECint / SPECfp
  • Summarizing

Types of Benchmarks

  1. Real program:
  2. Word processing software tool software of CDA user's application software (i.e.: MIS)
  3. Microbenchmark:
  4. Designed to measure the performance of a very small and specific piece of code.
  5. Kernel:
  6. 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
  7. Component Benchmark/ micro-benchmark:
  8. Programs designed to measure performance of a computer's basic components automatic detection of computer's hardware parameters like number of registers, cache size, memory latency
  9. Synthetic Benchmark:
  10. Procedure for programming synthetic benchmark: take statistics of all types of operations from many application programs get proportion of each operation write program based on the proportion above Types of Synthetic Benchmark Whetstone, Dhrystone. These were the first general purpose industry standard computer benchmarks. They do not necessarily obtain high scores on modern pipelined computers.
  11. I/O benchmarks
  12. Database benchmarks: to measure the throughput and response times of database management systems (DBMS')
  13. Parallel benchmarks: used on machines with multiple cores, processors or systems consisting of multiplemachines


This is the benchmark used to test the members of Top500 list.

The LINPACK Benchmark was introduced by Jack Dongarra. A detailed description as well as a list of performance results on a wide variety of machines is available in postscript form from netlib. Here you can download the latest version of the LINPACK Report: performance.ps. A parallel implementation of the Linpack benchmark and instructions on how to run it can be found at http://www.netlib.org/benchmark/hpl/.

The benchmark used in the LINPACK Benchmark is to solve a dense system of linear equations. TOP500 uses a version of the benchmark that allows the user to scale the size of the problem and to optimize the software in order to achieve the best performance for a given machine. This performance does not reflect the overall performance of a given system, as no single number ever can. It does, however, reflect the performance of a dedicated system for solving a dense system of linear equations. Since the problem is very regular, the performance achieved is quite high, and the performance numbers give a good correction of peak performance.

By measuring the actual performance for different problem sizes n, a user can get not only the maximal achieved performance Rmax for the problem size Nmax but also the problem size N1/2 where half of the performance Rmax is achieved. These numbers together with the theoretical peak performance Rpeak are the numbers given in the TOP500. In an attempt to obtain uniformity across all computers in performance reporting, the algorithm used in solving the system of equations in the benchmark procedure must conform to LU factorization with partial pivoting. In particular, the operation count for the algorithm must be 2/3 n^3 + O(n^2) double precision floating point operations. This excludes the use of a fast matrix multiply algorithm like "Strassen's Method" or algorithms which compute a solution in a precision lower than full precision (64 bit floating point arithmetic) and refine the solution using an iterative approach.

Top500: LinPack Benchmark

If you want to use Linpack in your system, follow these steps
  1. Download the LinPack Benchmark: LinPack 10.3.4
  2. Extract the content of the packet.
  3. Open the path: ~/linpack_10.3.4/benchmarks/linpack/
  4. Run the executable xlinpack_xeon64 or xlinpack_xeon32 according your architecture
  5. Set these inputs:
    Input data or print help ? Type [data]/help : data
    Number of equations to solve (problem size): 5000
    Leading dimension of array: 10000
    Number of trials to run: 10
    Data alignment value (in Kbytes): 1000000
  6. Press enter and wait to the finish
This is my output

There are also a package to run Linpack in HP Clusters, but I will review that when the cluster are ready :)


martes, 8 de mayo de 2012

[DPS Lab] Extra Points 3

  • Energy: is an indirectly observed quantity. It is often understood as the ability a physical system has to do work on other physical systems. Since work is defined as a force acting through a distance (a length of space), energy is always equivalent to the ability to exert pulls or pushes against the basic forces of nature, along a path of a certain length.
  • Storage: refers to computer components and recording media that retain digital data. Data storage is a core function and fundamental component of computers.
  • Attention: is the cognitive process of selectively concentrating on one aspect of the environment while ignoring other things. Attention has also been referred to as the allocation of processing resources.
  • Industry: is the production of an economic good or service within an economy.
  • Expert: is someone widely recognized as a reliable source of technique or skill whose faculty for judging or deciding rightly, justly, or wisely is accorded authority and status by their peers or the public in a specific well-distinguished domain.
  • Powerful: Having or capable of exerting power. Effective or potent.
  • Simulate: is the imitation of the operation of a real-world process or system over time.[1] The act of simulating something first requires that a model be developed; this model represents the key characteristics or behaviors of the selected physical or abstract system or process. The model represents the system itself, whereas the simulation represents the operation of the system over time.
  • Peak: The highest, or sometimes the highest and lowest points or value on some measurement, result, graph, etcetera.

domingo, 29 de abril de 2012

[DPS Class] Contributions WEEK 12

This week I did a research about High Availability Techniques in order for maintain the communications between the nodes of our cluster, in that research I include a very simple definitions, and some programs that we can use on our cluster.

  • Emmanuel.
  • Saul.
  • Alex
The references are in the page.


Para automatizar algunas tareas...