Construir red
¿que vamos a hacer con los datos del concurso? Lo primero, durante el verano, construir la red, claro. Registrando quienes se van apuntando al arbol, que estructura tiene, en que día se va añadiendo cada nodo, etc.
A partir de ahi, dependera de los tamaños alcanzados, para que sea suficientemente significativa para los cientificos y puedan modelizarla, y de la disponibilidad que percibamos de los participantes, en cuanto a arrancar otros experimentos a traves de la red montada o comparandola con las redes de ibercivis desplegadas en plataformas comerciales (recordad que estamos en facebook, tuenti, ...)
61 comentarios
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Alvaro -
Veo que vais haciendo mejoras en la forma de presentar los datos, pero bajo mi punto de vista es más importante hacer bien las clasificaciones. Y más cuando habéis metido un botón "premiados".
Por otra parte, ¿cuanta gente necesitais para que el experimento tenga éxito?. Creo que se está demostrando que los participantes en ibercivis están bastante inconexos entre ellos. Además como los email no son públicos (excepto para los fundadores de los equipos) y poca gente se pasa a leer los mensajes privados, se hace difícil el contacto.
Lo más fácil, se está viendo que es invitar a gente nueva que no participaba en el proyecto, pero que al ser nuevos obviamente no están tan implicados, no saben muy bien como funciona, las reglas del concurso se le hacen complicadas, etc... y así es difícil que inviten a gente nueva para que crezca el grafo.
No obstante, espero que se logre el éxito. En cuanto a redes sociales, a veces es necesario alcanzar una masa crítica para que el crecimiento se dispare de forma exponencial.
Ibercivis -
Álvaro -
Me han gustado los cambios que habéis hecho en el árbol y me gustaría haceros una sugerencia: Estaría bien que se mostraran los participantes nuevos en diferente color que los antiguos. Por ejemplo verde pálido los nuevos no activos, y verde saturado los nuevos activos.
Esto daría una información muy valiosa para seguir el concurso en las categorías en las que sólo cuentan los usuarios nuevos.
Saludos.
Ibercivis -
Manu -
Welcome to "CUDA: Week in Review," a weekly newsletter for the worldwide CUDA and GPU Computing community.
Contact us at: cuda_week_in_review@nvidia.com.
Follow us on Twitter: www.twitter.com/gpucomputing.
See previous issues: http://is.gd/cBXbg
Update on GTC 2010 (GPU Technology Conference)
We are pleased to welcome Adobe, HP, Microsoft, PNY, Supermicro and Dell as GTC
2010 Platinum Sponsors, and Cooley LLP as a GTC 2010 Emerging Companies Summit
Sponsor
GTC 2010 registration is now open!
Special code for "CUDA: Week in Review" readers - GMCUDANEWS10
CUDA NEWS
GPU Computing - At the Tipping Point
IEEE Computer Society has published an informative article about GPU Computing by NVIDIA's John Nickolls and Bill Dally. Here's the introduction:
"GPU computing is at a tipping point, becoming more widely used in demanding consumer applications and high-performance computing. This article describes the rapid evolution of GPU architectures (from graphics processors to massively parallel many-core multiprocessors), recent developments in GPU computing architectures, and how the enthusiastic adoption of CPU + GPU co-processing is accelerating parallel applications."
Read full article here: http://www.computer.org/portal/web/computingnow/0610/whatsnew/micro
Learn about MAGMA from the Experts
Professor Jack Dongarra and Dr. Stan Tomov of the University of Tennessee will present a webinar on "The MAGMA Project: Acceleration of Dense Linear Algebra on the GPU" on Monday, June 14 at 9:00 a.m. pacific. MAGMA (Matrix Algebra on GPU and Multicore Architectures) aims to develop a dense linear algebra library similar to LAPACK but for heterogeneous/hybrid architectures, starting with current "Multicore+GPU" systems.
Prof. Jack Dongarra has a deep background in the development, testing and documentation
of mathematical software. He has contributed to the design and implementation of open
source software including EISPACK, LINPACK, the BLAS, LAPACK, ScaLAPACK,
Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI. See bio:
http://www.netlib.org/utk/people/JackDongarra/
Dr. Stan Tomov has been involved in research and development for LAPACK/scaLAPACK,
multicore computing and MAGMA. Research interests include parallel algorithms and high
performance scientific computing. See bio: http://www.cs.utk.edu/~tomov/resume.html
Sign up for the MAGMA webinar here: https://www2.gotomeeting.com/register/565103979
This presentation is a feature of NVIDIAs ongoing series of webinars on GPU Computing
CUDA APPS
Attention Photographers: New Photoshop Plugin Powered by CUDA
Digital Anarchy, provider of software for photographers and digital artists, recently introduced "Beauty Box Photo" skin retouching software - the worlds first CUDA-accelerated Photoshop plugin. The software automatically smoothes skin and removes blemishes, saving photographers hours of time. It identifies skin tones and creates an intelligent mask to limit the smoothing effect to skin areas while keeping facial details sharp. Beauty Box Photo gets its render speed from new technology from Toonmation and leverages CUDA for up to 6X faster processing.
Read about Beauty Box Photo: http://www.digitalanarchy.com/beautyPS/main.html
Read about Digital Anarchy: http://www.digitalanarchy.com/
Read about Toonmation: http://toonamation.com/
GPU-Accelerated Imaging and Vision Processing
In March we introduced you to Canada-based DALSA, a leader in machine vision systems. At a recent event in Boston called "The Vision Show," DALSA announced that GPUs enable the "Sapera Nitrous" product to accelerate image processing for filters, point-to-point, color and other image/vision processing functions. DALSA products are used across applications from solar panel inspection to postal automation.
Read the press release: http://www.dalsa.com/mv/news/news.aspx?itemID=241
Learn more about Sapera Nitrous: http://www.dalsa.com/mv/products/Nitrous.aspx
CUDA ZONE
New on CUDA Zone: Acceleration of the Smith-Waterman Algorithm using GPUs
Application Domain: DNA/protein sequence testing
Authors: Ali Khajeh-Saeed, Univ. of Mass at Amherst; Stephen Poole, Oak Ridge National Lab; J. Blair Perot, Univ. of Mass at Amherst
Extract: "Finding regions of similarity between two very long data streams is a computationally intensive problem referred to as sequence alignment. Perhaps the most well known application of sequence matching is the testing of DNA or protein sequences against genome databases. The Smith-Waterman algorithm is a method for characterizing how well two sequences can be aligned . The results indicate that for large problems a single GPU is up to 45 times faster than a CPU for this application, and the parallel implementation shows linear speed up on up to 4 GPUs." See: http://is.gd/cJELx
CUDA Zone: Have a CUDA-related app or paper? Let us know when you post it on CUDA Zone and we'll send you a CUDA t-shirt!
CUDA JOB OF THE WEEK
KLA-Tencor, supplier of process control and yield management solutions, is seeking an algorithm engineer. The ideal candidate will have an M.S. or Ph.D. in Computer Science or Electrical Engineering, with a background in image processing or digital signal processing with an emphasis on computational algorithms, optimization and parallel computing. Experience using SIMD extensions or GPU programming (CUDA/OpenCL) is preferred. See: http://kla-tencor-jobs.blogspot.com/
CUDA EDUCATION
GPU Computing Webinars (CUDA C, OpenCL, Parallel Nsight and more )
See June webinar schedule: http://developer.nvidia.com/object/gpu_computing_online.html. Upcoming webinars include:
Intro to the MAGMA Project - Acceleration of Dense Linear Algebra
Monday, June 14, 2010, 9:00 a.m. pacific
Presented by Jack Dongarra and Stan Tomov, University of Tennessee
Intro to CULA GPU Accelerated Linear Algebra
Tuesday, June 15, 2010, 9:00 a.m. pacific
Presented by EM Photonics, advanced computing solutions provider
Rapid Application Development Platform for GPGPUs - Jacket / MATLAB
Tuesday, June 22, 2010, 8:00 a.m. pacific
Presented by AccelerEyes, developer of Jacket for MATLAB
Intro to MainConcept's CUDA H.264/AVC Encoder
Tuesday, June 29, 2010, 9:00 a.m. pacific
Presented by MainConcept, video and audio codec solutions provider
CUDA Training
CUDA training from Acceleware
July 26-30, Cambridge, Mass: www.acceleware.com/jul26cambridge (with Microsoft)
August 2-6, New York City: www.acceleware.com/aug02newyork (with Microsoft)
Sept. 13-17, Calgary: www.acceleware.com/sep13calgary
CUDA training from SagivTech
CUDA course: July 12-14, Raanana, Israel
GPU/Image Processing course: Aug. 2-4, Raanana, Israel
See: http://www.sagivtech.com/24054.html
CUDA training from EMPhotonics
On-site standard and customized training programs
See: http://www.emphotonics.com/services/cuda-training
CUDA Research and Certification
NVIDIA has launched new programs for GPU Computing developers. For more info, see: http://www.nvidia.com/object/io_1275409333119.html
CUDA and Academia
Over 350 universities are teaching CUDA and GPU Computing courses. We recently learned about a new course taught at the University of Jordan:
Course name: Parallel Computing
Location: University of Jordan in Amman, Jordan
Instructor: Dr. Walid Abu-Sufah
URL: http://www1.ju.edu.jo/ecourse/abusufah/cpe779_spr10/index.html
Lecture Notes: http://www1.ju.edu.jo/ecourse/abusufah/cpe779_spr10/lectures.htm
CUDA Center of Excellence Program
The CUDA Center of Excellence (CCOE) Program recognizes universities that are expanding the frontier of massively parallel computing using CUDA. See: http://research.nvidia.com/content/cuda-centers-excellence
CUDA CALENDAR
DoD High Performance Computing Modernization Program (HPCMP) Users Group
June 14-17, Schaumburg, IL
Note: Stan Posey of NVIDIA will be a panelist on "Current and Future Applications Using GPUs, FPGAs and Cell Processors for HPC"
http://www.hpcmo.hpc.mil/community/UGC/ugc2010/index.php
European Association of Geoscientists & Engineers (EAGE) Conference
June 14-17, Barcelona
http://www.eage.org/events/index.php?eventid=297
Parallel Execution of Sequential Programs on Multi-Core Architectures
June 20, Saint-Malo, France
http://cccp.eecs.umich.edu/pespma/cfp.html
GPGPU Briefing on Financial Services (Microsoft/NVIDIA)
June 21, New York, NY
https://msevents.microsoft.com/CUI/EventDetail.aspx?EventID=1032451443&culture=en-US
SIFMA Financial Services Tech Expo
June 22-24, New York, NY
http://events.sifma.org/2010/487/event.aspx?id=13584
High Performance Graphics 2010
June 25-27, Saarbrucken, Germany
http://www.highperformancegraphics.org
GPUs in Chemistry and Materials Science
June 28-30, Univ. of Pittsburgh
http://www.sam.pitt.edu/education/gpu2010.register.php
Parallel Symbolic Computation 2010 (PASCO)
July 21-23, Grenoble, France
http://pasco2010.imag.fr/contest.html
SIGGRAPH
July 25-29, Los Angeles
http://www.siggraph.org/s2010/
Virtual School of Comp. Science & Engineering Summer School
Aug. 2-6, choice of onsite locations
https://hub.vscse.org (Proven Algorithmic Techniques for Many-Core Processors)
Symposium on Chemical Computations on GPGPUs
Aug. 22-26, Boston
http://illinois.edu/lb/article/2101/36281
Unconventional High Performance Computing 2010 (UCHPC 2010)
Aug. 31-Sept. 1, Italy
http://www.lrr.in.tum.de/~weidendo/uchpc10/
GPU Technology Conference (GTC) 2010
Sept. 20-23, San Jose, Calif.
http://www.nvidia.com/gtc (now accepting proposals from industry and academia)
Supercomputing 2010
Nov. 13-19, New Orleans, LA
http://sc10.supercomputing.org/
IEEE International Parallel & Distributed Processing Symposium
May 16-20, 2011, Anchorage, AL
http://www.ipdps.org/
(To list an event, email: cuda_week_in_review@nvidia.com)
CUDA RESOURCES
CUDA Articles in Dr. Dobb's
Supercomputing for the Masses, Part 18: http://is.gd/cs6b9
Supercomputing for the Masses, Part 17: http://is.gd/cs6eI
Supercomputing for the Masses, Part 16: http://is.gd/citaC
Supercomputing for the Masses, Part 15: http://is.gd/citnJ
CUDA Books
Programming Massively Parallel Processors by D. Kirk, W. Hwu: http://is.gd/7bNYP
See additional books here: http://www.nvidia.com/object/cuda_books.html
CUDA Toolkit
Download CUDA Toolkit 3.0: http://bit.ly/aKCENp
CUDA Documentation
Download developer guides and documentation: http://developer.nvidia.com/object/gpucomputing.html
NVIDIA Parallel Nsight
Download the Parallel Nsight Beta: www.nvidia.com/nsight
Download the Parallel Nsight Beta Release Notes: http://bit.ly/9iEYMs
CUDA ON THE WEB
NEW: Check out the NVIDIA Research site: http://research.nvidia.com
Read previous issues of CUDA: Week in Review: http://is.gd/cBXbg
Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
Network with other developers: www.gpucomputing.net
Stayed tuned to GPGPU news and events: www.gpgpu.org
Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
Watch CUDA on YouTube: http://www.youtube.com/nvidiacuda
About CUDA
CUDA is NVIDIAs parallel computing hardware architecture. NVIDIA provides a complete toolkit for programming on the CUDA architecture, supporting standard computing languages such as C, C++, and Fortran as well as APIs such as OpenCL and DirectCompute.
Send comments and suggestions to: cuda_week_in_review@nvidia.com
Saludos
Álvaro -
Saludos.
Álvaro -
A mi me parece que es un concurso muy divertido. Más que el del año pasado (y no requiere dormir con el ordenador encendido para tener algún tipo de posibilidad :-) )
Espero que tengáis un gran éxito en este experimento.
Mario -
http://concurso.ibercivis.es/invitacion?invitation_code=28f1b4ab8ad840904e2284abefd5c17f