Archive for the ‘Scientific Computing’ Category

Scientific Computing and Numerical Analysis FAQ

Saturday, April 6th, 2013

Scientific Computing and Numerical Analysis FAQ

From the webpage:


Note: portions of this document may be out of date. Search the web for more recent information!

This is a summary of Internet-related resources for a handful of fields related to Scientific Computing, primarily:

  • scientific and engineering numerical computing
  • numerical analysis
  • symbolic algebra
  • statistics
  • operations research

Some parts may be out of date but it makes up an impressive starting place.

I first saw this in a tweet by Scientific Python.

Posted in Numerical Analysis, Scientific Computing | No Comments »

Hadoop in Perspective: Systems for Scientific Computing

Saturday, January 19th, 2013

Hadoop in Perspective: Systems for Scientific Computing by Evert Lammerts.

From the post:

When the term scientific computing comes up in a conversation it’s usually just the occasional science geek who shows signs of recognition. But although most people have little or no knowledge of the field’s existence, it has been around since the second half of the twentieth century and has played an increasingly important role in many technological and scientific developments. Internet search engines, DNA analysis, weather forecasting, seismic analysis, renewable energy, and aircraft modeling are just a small number of examples where scientific computing is nowadays indispensible.

Apache Hadoop is a newcomer in scientific computing, and is welcomed as a great new addition to already existing systems. In this post I mean to give an introduction to systems for scientific computing, and I make an attempt at giving Hadoop a place in this picture. I start by discussing arguably the most important concept in scientific computing: parallel computing; what is it, how does it work, and what tools are available? Then I give an overview of the systems that are available for scientific computing at SURFsara, the Dutch center for academic IT and home to some of the world’s most powerful computing systems. I end with a short discussion on the questions that arise when there’s many different systems to choose from.

A good overview of the range of options for scientific computing, where, just as with more ordinary problems, no one solution is the best for all cases.

Posted in Hadoop, Scientific Computing | No Comments »

2013 Workshop on Interoperability in Scientific Computing

Friday, September 28th, 2012

2013 Workshop on Interoperability in Scientific Computing

From the post:

The 13th annual International Conference on Computational Science (ICCS 2013) will be held in Barcelona, Spain from 5th – 7th June 2013. ICCS is an ERA 2010 ‘A’-ranked conference series. For more details on the main conference, please visit www.iccs-meeting.org The 2nd Workshop on Interoperability in Scientific Computing (WISC ’13) will be co-located with ICCS 2013.

Approaches to modelling take many forms. The mathematical, computational and encapsulated components of models can be diverse in terms of complexity and scale, as well as in published implementation (mathematics, source code, and executable files). Many of these systems are attempting to solve real-world problems in isolation. However the long-term scientific interest is in allowing greater access to models and their data, and to enable simulations to be combined in order to address ever more complex issues. Markup languages, metadata specifications, and ontologies for different scientific domains have emerged as pathways to greater interoperability. Domain specific modelling languages allow for a declarative development process to be achieved. Metadata specifications enable coupling while ontologies allow cross platform integration of data.

The goal of this workshop is to bring together researchers from across scientific disciplines whose computational models require interoperability. This may arise through interactions between different domains, systems being modelled, connecting model repositories, or coupling models themselves, for instance in multi-scale or hybrid simulations. The outcomes of this workshop will be to better understand the nature of multidisciplinary computational modelling and data handling. Moreover we hope to identify common abstractions and cross-cutting themes in future interoperability research applied to the broader domain of scientific computing.

How is your topic map information product going to make the lives of scientists simpler?

Posted in Conferences, Interoperability, Science, Scientific Computing | No Comments »

Tilera’s TILE-Gx Processor Family and the Open Source Community [topic maps lab resource?]

Thursday, June 21st, 2012

Tilera’s TILE-Gx Processor Family and the Open Source Community Deliver the World’s Highest Performance per Watt to Networking, Multimedia, and the Cloud

It’s summer and on hot afternoons it’s easy to look at all the cool stuff at online trade zines. Like really high-end processors that we could stuff in our boxes, to run, well, really complicated stuff to be sure. ;-)

On one hand we should be mindful that our toys have far more processing power than mainframes of not too long ago. So we need to step up our skill at using the excess capacity on our desktops.

On the other hand, it would be nice to have access to cutting edge processors that will be common place in another cycle or two, today!

From the post:

Tilera® Corporation, the leader in 64-bit manycore general purpose processors, announced the general availability of its Multicore Development Environment™ (MDE) 4.0 release on the TILE-Gx processor family. The release integrates a complete Linux distribution including the kernel 2.6.38, glibc 2.12, GNU tool chain, more than 3000 CentOS 6.2 packages, and the industry’s most advanced manycore tools developed by Tilera in collaboration with the open source community. This release brings standards, familiarity, ease of use, quality and all the development benefits of the Linux environment and open source tools onto the TILE-Gx processor family; both the world’s highest performance and highest performance per watt manycore processor in the market. Tilera’s MDE 4.0 is available now.

“High quality software and standard programming are essential elements for the application development process. Developers don’t have time to waste on buggy and hard to program software tools, they need an environment that works, is easy and feels natural to them,” said Devesh Garg, co-founder, president and chief executive officer, Tilera. “From 60 million packets per second to 40 channels of H.264 encoding on a Linux SMP system, this release further empowers developers with the benefits of manycore processors.”

Using the TILE-Gx processor family and the MDE 4.0 software release, customers have demonstrated high performance, low latency, and the highest performance per watt on many applications. These include Firewall, Intrusion Prevention, Routers, Application Delivery Controllers, Intrusion Detection, Network Monitoring, Network Packet Brokering, Application Switching for Software Defined Networking, Deep Packet Inspection, Web Caching, Storage, High Frequency Trading, Image Processing, and Video Transcoding.

The MDE provides a comprehensive runtime software stack, including Linux kernel 2.6.38, glibc 2.12, binutil, Boost, stdlib and other libraries. It also provides full support for Perl, Python, PHP, Erlang, and TBB; high-performance kernel and user space PCIe drivers; high performance low latency Ethernet drivers; and a hypervisor for hardware abstraction and virtualization. For development tools the MDE includes standard C/C++ GNU compiler v4.4 and 4.6; an Eclipse Integrated Development Environment (IDE); debugging tools such as gdb 7 and mudflap; profiling tools including gprof, oprofile, and perf_events; native and cross build environments; and graphical manycore application debugging and profiling tools.

Should a topic maps lab offer this sort of resource to a geographically distributed set of researchers? (Just curious. I don’t have funding but should the occasion arise.)

Even with the cloud, thinking topic map researchers need access to high-end architectures for experiments with data structures and processing techniques.

Posted in Multi-Core, Researchers, Scientific Computing, Topic Maps | No Comments »

Metadata Management in Scientific Computing

Tuesday, March 20th, 2012

Metadata Management in Scientific Computing by Eric L. Seidel.

Abstract:

Complex scientific codes and the datasets they generate are in need of a sophisticated categorization environment that allows the community to store, search, and enhance metadata in an open, dynamic system. Currently, data is often presented in a read-only format, distilled and curated by a select group of researchers. We envision a more open and dynamic system, where authors can publish their data in a writeable format, allowing users to annotate the datasets with their own comments and data. This would enable the scientific community to collaborate on a higher level than before, where researchers could for example annotate a published dataset with their citations.

Such a system would require a complete set of permissions to ensure that any individual’s data cannot be altered by others unless they specifically allow it. For this reason datasets and codes are generally presented read-only, to protect the author’s data; however, this also prevents the type of social revolutions that the private sector has seen with Facebook and Twitter.

In this paper, we present an alternative method of publishing codes and datasets, based on Fluidinfo, which is an openly writeable and social metadata engine. We will use the specific example of the Einstein Toolkit, a shared scientific code built using the Cactus Framework, to illustrate how the code’s metadata may be published in writeable form via Fluidinfo.

There are a number of interesting aspects to the proposal, such as nodes that collect tags but have no ownership or semantics. Not to mention that metadata can be made not only readable but writeable by others. I would disagree with ever allowing recorded metadata to change but that is a debatable point.

This is a rare paper that concludes:

Scienti c research is increasingly dependent on the simulation of complex processes and, by extension, on the ability to organize, search, and refer to the datasets generated by simulations. We propose using writable metadata to distribute and maintain scienti c metadata, and have shown one possible method of implementing such a system. More work will be required to investigate alternative systems, schemas, and interfaces, as well as to determine what would be an optimal solution. We hope that the scienti c community will take this opportunity to start a conversation about how to manage the large amounts of data currently being generated by our research on a daily basis.

A little spirit of continuing investigation goes a long way.

Posted in HPC, Metadata, Scientific Computing | No Comments »

IFIP Working Conference on Uncertainty Quantification in Scientific Computing

Saturday, October 29th, 2011

IFIP Working Conference on Uncertainty Quantification in Scientific Computing

From the webpage:

I just came across the following presentations at the IFIP Working Conference on Uncertainty Quantification in Scientific Computing held at the Millennium Harvest House in Boulder, on August 1-4, 2011. Here are the talks and some abstracts:

I really like the title of this blog: The Robust Mathematical Modeling Blog …When modeling Reality is not an option.

I think you will find the presentations good starting points for reviewing what we know or suspect about uncertainty.

Does anyone know of references to modeling uncertainties in the humanities?

Seems to me that our notions of subject identity should be understood along a continuum of uncertainty.

Posted in Scientific Computing, Uncertainty | No Comments »