Tag: petascale
Xinhua: Supercomputer Tianhe is a great success for China
China’s world-leading new supercomputer, Tianhe-1A, had shown the world what could be done using general-purpose computing on graphics processing units (GPGPUs), a German expert said
Altair Unveils PBS Pro 11, optimized for petascale and GPUs
Altair Engineering, Inc., a global leader in software solutions that make high-performance computing (HPC) faster, simpler and smarter, announced today the upcoming release of PBS Professional 11.0. More information will be announced at its Supercomputing 2010 (SC10) exhibit in New Orleans, La., Nov. 13-19, 2010.
LLNL Selects Appro’s Hybrid Blade Clusters to Support Data Analysis and Visualization Projects
Appro, a leading provider of supercomputing solutions, today announces the deployment of Appro HyperPower™ Clusters, based on the Appro CPU/GPU GreenBlade System to provide Lawrence Livermore National Laboratory (LLNL) Computing Center with a new visualization cluster called “Edge” geared to support data analysis and visualization projects.
NVIDIA Tesla GPUs Power World’s Fastest Supercomputer
Tianhe-1A, a new supercomputer revealed today at HPC 2010 China, has set a new performance record of 2.507 petaflops, as measured by the LINPACK benchmark, making it the fastest system in China and in the world today.
HP Builds GPU-Optimised Server
Hewlett-Packard has endorsed the use of graphics processing units (GPUs) for faster, cheaper scientific processing, and launched a modular processing system which uses them to pack 1 TeraFLOPS per unit of rack space.
Cray colaborating with Nvidia for GPU-based XE6 blades
Cray announced that it is developing blades based on the Nvidia Tesla 20-Series GPUs for use in the Cray XE6 product line. The combination of Cray’s new Gemini system interconnect paired with Nvidia GPUs will give Cray XE6 customers a powerful combination of scalability and production-quality GPU-based HPC in a single system.
An Experimental Distributed Visualization System for Petascale Computing
Modern computational science is increasingly producing largescale data sets using high-performance computing (HPC) resources that are remote from the user, making interactive visualization and analysis of such data a challenging task. The coming era of petascale computing and heterogeneous platforms calls for fundamental changes in perspective on how we design distributed visualization software.
