Development by Davis: “Steam for Linux gets three new games” plus 4 more

Steam for Linux gets three new games
Very Urgent Required : Author-IT Specialist for Qatar
Check single file size
A “Best Paper” on Big Data Signal Processing (Intel Labs@SC12)
Finding Meaning Among Billions of Galaxies (Intel Labs@SC12)

Posted: 16 Nov 2012 01:00 AM PST

Steam is a great source for any gamer. It is a place that will allow you to try out and enjoy many of the more popular video games that are available on the market today. Steam Greenlight will allow you to vote on games that you would like to see become available. It is a great system for gamers; they do not have to drop $50 to purchase every game off the shelf. They can simply join Steam and enjoy the most popular ones at a reduced price.

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Very Urgent Required : Author-IT Specialist for Qatar

Posted: 16 Nov 2012 06:24 AM PST

VAM SYSTEMS is a Business Consulting, IT Solutions and Services
company with operations in UAE, Qatar, Bahrain, USA, Australia,
Singapore & India.

VAM SYSTEMS is currently looking for Author-IT Specialist for our
Qatar operations with the following skill set and terms and
conditions:

Skill Set required:

Check single file size

Posted: 15 Nov 2012 09:44 PM PST

I am just getting started in powershell, (have been using DOS batch files so
far.)

I would like some assistance to write a simple batch file to check the file
size of a specific file. The file is not allowed to be more than 5gb.

The steps are therefore

1. Set Max_file_size = 5gb
2. Set warning_level = 10%

A “Best Paper” on Big Data Signal Processing (Intel Labs@SC12)

Posted: 15 Nov 2012 01:02 PM PST

It was just announced at the awards session at SC12 that Intel has won "best paper" for research into more efficient processing for a fundamental calculation in high performance computing, entitled "A Framework for Low-Communication 1-D FFT."

Numerous wave applications (e.g. sound, radio) rely on the Fast Fourier Transform (FFT) including signal processing, communications, and multi-media. However, it is a very challenging problem to parallelize effectively. This is because for big FFT datasets running on large clusters, 50%-90% of time can be spent waiting on node-node data transfers rather than useful calculation.

Intel's Software and Services Group & Intel Labs devised a new framework for distributed 1-D FFT problems which traditionally require three costly all-to-all inter-node data exchanges. The new approach delivers multiple 1D FFT algorithms requiring just a single all-to-all inter-node data exchange. According to the research, for large-scale problems this can double FFT performance (see the paper for details). Another key feature is that users can opt to further increase FFT performance by accepting reduced-accuracy results, so the algorithms scale to fit the needs of the particular application.

This posting includes an audio/video/photo media file: Download Now

Finding Meaning Among Billions of Galaxies (Intel Labs@SC12)

Posted: 15 Nov 2012 12:42 PM PST

As we speak, scientists are racing to apply Big Data computation techniques to help answer some of the most fundamental questions about the origin, composition, and evolution of the universe. A large part of this is the quest to understand dark matter and dark energy. These are thought to comprise as much as 96% of the universe but are undetectable through normal means – hence the term 'dark'.

The answer may lie in Big Data — the ability to simultaneously correlate the movements of vast numbers of galaxies and find patterns that unlock these darkest of secrets in the universe. The challenge is keeping up with the data. In recent decades, the observed and simulated datasets have grown from a few dozen objects to billions. With the advent of bigger and faster telescopes there is no end in sight for the exploding data. Performing the necessary algorithm (called the Two Point Correlation Function or TPCF) today on a billion galaxies would take a single processor 50 years to analyze — and even today's supercomputers are hard pressed to keep up. The computational requirements are expected to grow further, well into the domain of Exascale computing. This is the subject of an ACM Gordon Bell Prize – nominated SC12 paper from Intel this week.

Intel Labs, in collaboration with Lawrence Berkeley National Laboratory (LBNL) and the University of California, Berkeley (and in support of their ISAAC project) has demonstrated new techniques to significantly accelerate the computation of TPCF on these immense datasets and reduce both the cost and energy of the quest of cosmic understanding. This approach is comprised of three components: 1) the ability to effectively distribute and manage the work across tens of thousands of Intel® Xeon® compute cores, 2) more efficient use of the SIMD (single compute on multiple data) capabilities within each Intel Xeon core, and 3) more efficient communications among the compute nodes.

This technique was tested on a 1.7 billion object dataset (provided via a collaboration between LBNL and the University of Sussex) using Lawrence Livermore National Laboratory's Zin computer, a Petascale-class machine with 1600 nodes each containing two Intel Xeon processors. The calculation was completed in just over five hours — more than 35 times faster than previous approaches (see notices below). This means scientists will be able to use this technique to complete experiments in a single day rather than weeks. In addition, the experiment demonstrated an 11x improvement in cost efficiency (measured in flops/$), making these experiments more practical and affordable.

More recently on the Texas Advanced Computing Center's Stampede cluster, a Petascale computer using Intel® Xeon Phi™ Coprocessors (launched this week), Intel Labs achieved a further speedup in run-time of 3.2 X on each node in comparison to the results above (see notices below).

This technique provides a path to computing even larger datasets into the Exascale domain, where new answers to many cosmological questions may be found within the next decade.

Legal Notices:

Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to http://www.intel.com/performance
Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. Notice revision #20110804

Development by Davis