To accelerate design and product development, and reduce time-to-market, manufacturing organizations are increasingly relying on IT to deliver infrastructure for simulations with increased model sophistication and detail. These simulations drive the need for faster compute that traditional dual- and quad-processor systems, with their limited memory, can no longer meet. To overcome these system limitations, software vendors have increasingly invested in scaling their applications to take advantage of the largest CPU solutions. These can be run either on shared memory processing (SMP) systems or on distributed memory systems (clusters). Market analysis shows that, when taking into account application scalability and software-licensing models, optimum system configurations are in the range of 4- to 16-processor and 128 GB to 512 GB. This makes solutions based on ScaleMP’s vSMP Foundation aggregation platform an ideal choice for these environments.

Computational chemistry shortens the development cycle for new drugs, and can save millions of dollars through early-stage simulations. Significant improvements in computer hardware and software allow researchers to perform highly complex analysis; predicting the properties of new chemical compounds and materials before any laboratory effort.

Computational structural and chemical analysis is not new and many applications have been developed over the years. A significant characteristic of this type of work is that scientists use a variety of different applications, including commercial, in-house custom, legacy and parallel applications using OpenMP, PVM, MPI and other types of message passing architectures. As such, computational chemists require well-balanced systems that are flexible and can run different application types. Solutions based on vSMP Foundation are ideal for these environments. The shared memory architecture can run all these applications with good performance, sometime leveraging the large compute, memory, or bandwidth configurations or a combination of each.

Solutions based on vSMP Foundation provide high performance coupled with lower management costs. They are particularly well suited in environments where computational chemists do not have dedicated IT staff or need to publish results fast for new innovative applications.

In addition to the challenges of exploring, extracting, refining and delivering energy sources they are also grappling with fluctuating margins, challenging political environments, regulatory constraints and capacity pressures. To succeed in such a difficult environment, Energy companies have turned to solutions based on vSMP Foundation across the entire workflow: to increase production yields, discover new energy sources, and run simulations. As with other industries, solutions based on vSMP Foundation have the advantage of offering high memory and memory bandwidth required by most reservoir and volume interpretation applications and the higher number of processors required by the seismic processing applications. In addition, leveraging the power of commodity x86 infrastructure coupled with the significantly lower costs of system hardware provides the high performance they expect and the significantly lower costs Energy companies appreciate.

In addition to the challenges of exploring, extracting, refining and delivering energy sources they are also grappling with fluctuating margins, challenging political environments, regulatory constraints and capacity pressures. To succeed in such a difficult environment, Energy companies have turned to solutions based on vSMP Foundation across the entire workflow: to increase production yields, discover new energy sources, and run simulations. As with other industries, solutions based on vSMP Foundation have the advantage of offering high memory and memory bandwidth required by most reservoir and volume interpretation applications and the higher number of processors required by the seismic processing applications. In addition, leveraging the power of commodity x86 infrastructure coupled with the significantly lower costs of system hardware provides the high performance they expect and the significantly lower costs Energy companies appreciate.

Nuestro compromiso con el el I D en España nos lleva a adquirir compromisos diferenciales con estos clientes y realizar esfuerzos adicionales con vistas a facilitar en lo posible el acceso de las últimas tecnologías en supercomputación a nuestro tejido investigador.

El CX1 es el complemento ideal para oficinas y departamentos que no tengan acceso por disponibilidad inmediata o problemas de seguridad a grandes infraestructuras nacionales de superconmputación.

Ejemplos de herramientas: SW de procesamiento de imagen de resonancias magnéticas, Jaguar (Schrödinger), Materials Studio (Accelrys)

Las empresas que pueden hacer aprovecharse de la ventaja competitiva de la supercomputación pertenecen a un amplio abanico que abarca el sector aeronaútico, la automoción, el CAD-CAM o la industria de semiconductores.

Ejemplos de herramientas: Múltiples de ANSYS, NASTRAN, SIMULIA.

El CX1 es una herramienta ideal para empresas petroleras y gaseras o agencias implicadas en la investigación energética.

Ejemplos de herramientas: GeoProbe (Landmark), Voxel Geo (Paradigm Geophysical), Eclipse(Schlumberger), Tempest (Roxar)