Windows 10: Nvidia Tesla K10 GPU - Errorcode 12

Hello, I just got my hands on two NVIDIA Tesla K10 GPUs that I wanted to put in my PC. (Its a MacPro 5.1 running bootcamp btw). Since the K10 is a dualGPU, the device manager shows 4 Tesla K10s. However, only one chip of each GPU works, the other one does not and always says "Code 12" in taskmanager.

So far I've tried: different PCIE Slots, installing the official Nvidia driver (5 times), DDUing the old drivers and even resettet the PC, but nothing worked.

If you have any Idea on what I can try to get this working, please let me know, I am stuck with this issue for almost 2 days now, thanks

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NVIDIA Tesla K10 GPU Hits New Performance Milestones For Scientific Simulation

ISC'12 - NVIDIA Tesla K10 GPUs offer performance breakthroughs on popular high performance computing (HPC) applications -- ranging from seismic processing to life sciences to video processing -- according to new benchmarks NVIDIA released today.

Based on the new NVIDIA Kepler computing architecture, the Tesla K10 GPU delivers the industry's highest single precision performance (4.58 teraflops) and highest memory bandwidth (320 GB/sec) in a single accelerator. This is 12 times higher single precision flops and 6.4 times higher memory bandwidth than the latest-generation Intel Sandy Bridge CPUs.





The Tesla K10 GPU outperforms CPUs and previous-generation GPUs across the board on the most popular, compute-intensive applications for four key market segments, including:

• Defense: video analytics, video stabilization, orthorectification, computer vision
• Life and material sciences: molecular dynamics
• Oil and gas: seismic processing, reverse time migration
• Media and entertainment: video editing, video rendering/transcoding, ray tracing

"A distinct advantage of the Tesla K10 GPUs is that it excels in two key areas that have a dramatic impact on overall application performance: floating point operation and memory bandwidth," said Sumit Gupta, senior director of Tesla business at NVIDIA. "Together, these enable the K10 GPU to deliver substantial out-of-the-box performance increases for the top science, engineering and commercial applications with little or no effort on the part of the developer."

New Performance Records on AMBER and LAMMPS
On AMBER, a leading biomolecular simulation software application, four Tesla K10 GPUs achieved world record performance, delivering far superior results than what was available on multiple racks of servers just a few years ago.

The Tesla system achieved performance of 76 nanoseconds of computer simulation time in a day for a 23,558 atom molecule, outstripping the previous record set with four Tesla M2090s last year, providing supercomputing performance to thousands of individual researchers to fuel further innovation in such areas as new drug discovery and more effective materials.

"In biomolecular science, adding a few more nanoseconds of simulation time can make a world of difference in the ability of researchers to study and better understand the behavior of complex biological systems," said Ross Walker, assistant research professor, San Diego Supercomputing Center. "It still blows my mind that a single Tesla K10 outperforms some of the largest CPU clusters. The benefit it offers researchers is tremendous, enabling them to accelerate the search for new and better treatments for a host of diseases and disorders."

The Tesla K10 GPU also delivers the highest performance on LAMMPS, another application widely used by the life sciences research community. Running the LAMMPS Lennard Jones Liquid Benchmark, a single Tesla K10 GPU outperforms a Tesla M2090 GPU by 80 percent, delivering the equivalent performance of a cluster with 64 x86 CPUs.

Accelerating the Search for Energy
NVIDIA Tesla GPUs continue to deliver the highest performance on reverse time migration (RTM) applications for seismic processing in the oil and gas exploration industry, and for image processing in the computer vision industry. Petrobras, the national oil and gas company of Brazil, achieved an 1.8x speed up on its RTM application on the Tesla K10 GPU, as compared to a Tesla M2090 GPU within the same power envelope.

NVIDIA Tesla K10 GPUs are available from leading OEMs, including Appro Supercomputer Solutions, Dell, HP, IBM, SGI and Supermicro, as well as through NVIDIA distribution partners. More information about the Tesla K10 is available on the NVIDIA Tesla website.

 

SGI Expands Rackable Server Line to Support New NVIDIA Tesla K10 GPUs

SGI, the trusted leader in technical computing, today announced the availability of a complete, managed GPU solution of its SGI Rackable servers with the new high-performance NVIDIA Tesla K10 GPU Computing Accelerator. Coupled with SGI Management and Performance Suite software, the solution is built, completely integrated, and tested in SGI's manufacturing facility so that it can be installed at the customer site and begin running application codes in less than a day.

The next-generation NVIDIA Tesla K10 GPU Accelerator is designed for throughput and performance per watt. It features two ultra-efficient GK104 GPUs that provide up to 2X performance per watt for single precision applications than its predecessor, the M2090. The NVIDIA Tesla K10 features two GK104 GPUs with 1536 CUDA cores each and 4 GB of memory operating at 160 GB/second per GPU. These GPUs are shown to be particularly well suited to single high precision workloads, including seismic processing, signal, image and video analysis, and radio astronomy.







"The research team at the Swinburne University of Technology has benefited from significant improvements in processing power and research output since our SGI Rackable system was installed in July 2011," said Dr. Jarrod Hurley, manager of Swinburne's supercomputer. "That system was over ten times more powerful than its predecessor, and with the introduction of the new NVIDIA Tesla K10 GPU Computing Accelerator we'll look forward to building even greater functionality and performance into our own system as our requirements evolve."

The baseline server for the solution is the SGI Rackable C1104G-RP5, a 1U standard depth chassis, and the SGI 2110-RP5, a 2U standard depth chassis. Each server features one dual-socket server powered by two Intel Xeon processor E5-2600 series, and 8 DIMM slots. The C1104 can accommodate up to four 2.5 inch hard disk drives, three PCI-E 3.0 x 16 double-width expansion slots and dual-port GigE networking controllers, while the C2110 can accommodate up to ten 2.5 inch hard drives, four internal PCI-E 3.0 x 16 double-width expansion slots and dual-port GigE controllers. SGI is also announcing the availability of the SGI GPU Starter Kit with NVIDIA Tesla K10 GPU Accelerator offering a pre-configured bundle of 10 nodes.

"As a leader in design-to-order high performance computing (HPC) solutions with over three decades of experience in accelerators applied to high precision workloads, SGI is uniquely positioned to bring its customers hybrid solutions of industry-standard microprocessors with GPU accelerators," said Bill Mannel, vice president of product marketing at SGI. "Our GPU clusters are all you need for a powerful deployment. We're also announcing the SGI GPU Starter Kit, a 10-server cluster with 20 NVIDIA Tesla K10 GPUs for those who want to start enjoying the benefits of CUDA programming today in a cost-effective solution."

"Adding GPUs to a server delivers significant application acceleration, and this is having a profound effect on many important industry segments," said Sumit Gupta, senior director of the Tesla business at NVIDIA. "SGI's new K10-enabled SGI Rackable servers provide researchers with a powerful and flexible platform upon which to innovate."

Availability
The NVIDIA Tesla K10 GPU is available in the SGI Rackable C1104G and C2110G server product lines. The SGI GPU Starter Kit with NVIDIA Tesla K10 GPU Accelerator is available in the SGI Rackable C1104G server product line. All are available for order today.

 

NVIDIA Tesla K10 GPU Hits New Performance Milestones For Scientific Simulation

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