1 / 10

Computación de Alto Rendimiento en IBM Research Septiembre 2006

Computación de Alto Rendimiento en IBM Research Septiembre 2006. Dr. José G. Castaños castanos@us.ibm.com IBM T.J. Watson Research Center. El Projecto “Blue Gene”. En Diciembre 1999, IBM Research anuncia el Blue Gene Producir nuevos adelantos en simulaciones biomoleculares

zaza
Download Presentation

Computación de Alto Rendimiento en IBM Research Septiembre 2006

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Computación de Alto Rendimientoen IBM ResearchSeptiembre 2006 Dr. José G. Castaños castanos@us.ibm.com IBM T.J. Watson Research Center

  2. El Projecto “Blue Gene” • En Diciembre 1999, IBM Research anuncia el Blue Gene • Producir nuevos adelantos en simulaciones biomoleculares • Investigar nueva tecnologias en hardware y software para producir computadoras de alto rendimiento • Blue Gene sigue un enfoque modular, donde el bloque basico (o célula) puede copiarse ad infinitum • Procesadores de bajo consumo – permite rendimientos combinados mas altos • PowerPC 440 • System-on-a-chip ofrece ventajas en costo/rendimiento • Menor complejidad • Alta densidad (2048 procesadores por rack, enfriado por aire) • Redes integradas para gran escala • Ambiente de software familiar, simplificado para HPC • Mucha atención a RAS (“reliability, availability, and serviceability”) en todo el sistema

  3. El Chip Blue Gene/L (ASIC) • IBM CU-11, 0.13 µm • 11 x 11 mm die size • 25 x 32 mm CBGA • 474 pins, 328 signal • 1.5/2.5 Volt

  4. Arquitectura de Blue Gene/L

  5. Blue Gene/L en Lawrence Livermore National Laboratory

  6. Blue Gene en los Top500 Source: www.top500.org

  7. Motivacion del Software de Sistema • Nodos de Computación dedicados a ejecutar una sola aplicacion, and casi nada más • Compute node kernel (CNK) • Simplicidad! • Nodos de I/O corren Linux and proveen servicios de OS – files, sockets, comenzar programas, señales, debugging, and fianalización de tareas • Solution estandar: Linux • Nodos de Servicio ejecutan todos los servicios de administración (e.g., latidos, checkean errores) • transparente para el programa de los usuarios

  8. C-Node 63 C-Node 63 C-Node 0 C-Node 0 CNK CNK CNK CNK Blue Gene/L: Architectura del Software de Sistema tree Pset 0 Service Node I/O Node 0 SystemConsole Front-endNodes FileServers Linux app app fs client ciod Functional Gigabit Ethernet CMCS torus DB2 I/O Node 1023 Linux I2C app app Control GigabitEthernet LoadLeveler fs client ciod IDo chip JTAG Pset 1023

  9. 2,048,000 Tantalum atoms Classical MD – ddcMD2005 Gordon Bell Prize Winner!! • Scalable, general purpose code for performing classical molecular dynamics (MD) simulations using highly accurate MGPT potentials • MGPT semi-empirical potentials, based on a rigorous expansion of many body terms in the total energy, are needed in to quantitatively investigate dynamic behavior of d-shell and f-shell metals. 524 million atom simulations on 64K nodes achieved 101.5 TF/s sustained. Superb strong and weak scaling for full machine - (“very impressive machine” says PI) Visualization of important scientific findings already achieved on BG/L: Molten Ta at 5000K demonstrates solidification during isothermal compression to 250 GPa

  10. Resolidificación Rapida del Tantalum (ddcMD) Nucleation of solid is initiated at multiple independent sites throughout each sample cell Growth of solid grains initiates independently, but soon leads to grain boundaries which span the simulation cell: size of cell is now influencing continued growth 2,048,000 simulation recently performed indicates formation of many more grains

More Related