November 20, 2006
eXludus Technologies Inc. introduced version 2.1 of RepliCator, the company's software product for compute clusters and grids.
"RepliCator 2.1 adds two important capabilities that are world firsts," said eXludus Technologies CEO Benoît Marchand. "Our new features, Asynchronous Results Transfer (ART) and Groups, expand the range of applications for which RepliCator can substantially boost performance. ART can make an important difference in the manufacturing, life sciences, financial services, EDA and public sector research markets, as well as in high performance computing wherever checkpoints or output data sets are bottlenecks today."
According to eXludus, RepliCator 2.1 is the world's first cluster/Grid software to provide fault-tolerant and data resilient data transfer from any source to any destination. RepliCator's Asynchronous Results Transfer (ART) capability can be applied to output files (e.g., intermediate results, checkpoints, final results) or to input files.
On a real-world workload using checkpoint files, Durham University's Institute for Computational Cosmology (UK) improved cluster throughput by a factor of 1.48 by using RepliCator to allow overlapping of output checkpoint data movement with computation. Wall clock time was reduced from 445 seconds to 301 seconds, and I/O wait time shrank from 145 seconds to 0.1 seconds
"It doesn't matter what the underlying application is. If it involves large files and is doing substantial checkpointing on a medium to large-size cluster, RepliCator's new ART feature can make a major difference," said Marchand.
With ART, data can be transferred at the end of a task automatically, using eXludus's MetaLanguage Processor, or manually through a command-line interface, or on-the-fly through the API interface. RepliCator allows the compute nodes to get back to what they do best -- run your simulation.
RepliCator 2.1 also offers the ability for parallel file serving of an input file to a targeted subset of cluster nodes, as opposed to the entire cluster. With RepliCator 2.1's new Groups feature, the cluster subset can be made to match the workload manager's group definition (e.g., "Send this Nastran input file to Nastran nodes"). The Groups feature allows an unlimited number of groups to be used concurrently on a cluster.
"Groups allows RepliCator to operate in multi-application clusters more efficiently, by caching data only on likely target nodes, those that are candidates to run certain job types," according to Marchand.
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
May 10, 2013 |
Australian visual effects company, Animal Logic, is considering a move to the public cloud.
May 10, 2013 |
Program provides cash awards up to $10,000 for the best open-source end-user applications deployed on 100G network.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.