imann - Slashdot User

Submission + - The most expensive X86 server ever built !

Submitted by imann on Friday October 30, 2009 @06:55AM

imann writes: Dell have been introduced in its online configuration tool an option called "Multiquantity" for selecting several time the same item. On the European version of it, they didn't had implemented any control on the amount of items you can select.
This lead to strange situation where you can create servers with unrealistic configurations. This bug is kind of scary as he doesn't prevent you from creating stupid configurations like 9 disks instead of 8 supported. While pushing this bug to the extreme, you can have servers costing thousands of billons dollars (54 798 980 004 128€ in my case) !

To be honest and remove OS/browser bugs, I've been able to reproduce that on IE/Firefox Linux/Windows. This screenshots were done under Windows Vista (in kvm) + IE 8.

Here come some screenshots :
http://pubz.free.fr/sd/2U_le_plus_cher_du_monde.png
http://pubz.free.fr/sd/2U_le_plus_cher_du_monde_2.png

Submission + - Nvidia launch the era of GPU computing

Submitted by imann on Wednesday July 18, 2007 @11:20AM

imann writes: Regarding http://www.nvidia.com/object/tesla_computing_solut ions.html, nvidia open a new era in the high performance computing.
The new brand called Tesla contains a GPU computing processor, a workstation and a 1U server. The workstation owns 2 GPU and the server 4.
NVidia provides also a software environment called CUDA made of a C-compiler, a FFT and a BLAS library and some sample codes for various computing needs (matrix, imaging, etc..). Some optional modules are available for some specific computing code like monte-carlo, Black-Scholes, binomial operations, matlab. Some like matlab sounds to be free whereas you need to buy the others.

What's sounds very impressive in such approach is the power you can expect from this "GPU computing". Regarding Nvidia's spec, the GPU offer 128-processor computing core connected to 1.5 GB of GDDR3 memory that deliver 76.8 GB/sec due to a very large bus (384-bit). This configuration provides (still regarding nvidia's spec) a 500 gigaflops peak... This surely be achieved only with a massively distributed program BUT if scientists are able to reach this performance it looks incredible... Just imagine a P4 or a cell processor can only reach 14Gflops (http://de.wikipedia.org/wiki/Floating_Point_Opera tions_Per_Second). If now you realize that a 1U Telsa server offer 4GPU, it could theoretically reach 2 TeraFlops...

All this stuff seems to start a new era for HPC computing. Using the GPU computing (with some rewritten code) will surely open new doors to scientist to reach real-time computing or to faster cpu-intensive application like genomic.

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