Acceleware Blog

NVIDIA Hardware Comparison – GeForce GTX 690 vs. Tesla K10

GeForce GTX 690 vs. Tesla K10

During a recent webinar one of our attendees asked us the question:

“Which hardware is faster – the GeForce GTX 690 or the Tesla K10?”

The short answer: GeForce GTX 690.

That isn’t the entire story though. The specifications for both cards are shown in the table below:

Card Number of GPUs Memory BW (GB/s) SP Performance (GFlops) Memory (GB) Power (W) Cooling
GTX 690 2 (GK104) 284.5 5622 4 300 Fan
K10 2 (GK104) 320 4577 8 250 Passive

While the raw throughput on the GeForce GTX 690 is higher than the Tesla K10, the memory on the GTX 690 is half of the size of the K10. Depending on your application, memory size may outweigh the benefit of the slightly higher throughput on the GeForce.

Additionally, NVIDIA’s Tesla product line has features not available for GeForce hardware:

  • ECC Memory Protection – improved memory reliability
  • Manufacturing Quality – hardware is manufactured and tested by NVIDIA to guarantee highest reliability
  • 1.5 to 2 Year Availability – useful for enterprise customers who need to replace or add hardware after initial deployment
  • Cluster and GPU Management Software – diagnostics useful for monitoring hardware in clusters
  • Advanced Driver Support – TCC drivers allows the use of Windows Remote Desktop and avoids the Windows watchdog timer when running large kernels
  • Form Factors – Tesla is supported in certified servers, blades and workstations

The full list of Tesla benefits can be found here:

In almost all cases, our customers deploy Tesla hardware in production environments. The memory size, reliability and long availability outweigh the modest performance benefits of the GeForce product line.

Finally, for double precision computations you will want to consider the K20X or GeForce GTX Titan since the double precision performance on the GTX 690 and K10 is approximately 1/24th the single precision throughput. But if you can get away with single precision calculations, the GeForce GTX 690 and Tesla K10 are great hardware choices!


Does your CUDA application need to target a specific GPU? If you are writing GPU enabled code, you would typically use a device query to select the desired GPUs. However, a quick and easy solution for testing is to use the environment variable CUDA_VISIBLE_DEVICES to restrict the devices that your CUDA application sees. This can be useful if you are attempting to share resources on a node or you want your GPU enabled executable to target a specific GPU.

GTC, San Jose 2012

This year at NVIDIA’s GPU Technology Conference in San Jose, I had the privilege of hosting a CUDA™ workshop to over 200+ attendees. Throughout the day we covered topics including GPU memory management, debugging, and optimizations. The questions from the audience were very insightful and addressed important aspects of GPU programming. I would like to thank Kiran and Ramesh who were able to help me on stage with the code demonstrations. The feedback from attendees was very positive and I look forward to hosting additional seminars at upcoming conferences.

Cell Phones in the News

SAR, Cell Phones, and San Francisco

Design Automation Conference 2009

I had the opportunity to visit DAC 2009 this year in San Francisco. DAC is an EDA conference which showcases tools and processes that perform simulation, logic synthesis, design verification, and timing analysis.  The work we do in linear algebra has direct applicability in this space, and we are eager to expand our reach in the EDA market. The show itself was well attended and there were approximately 200 exhibitors. It was great to catch up with our customers and reach out to some new ones.

IMS 2009 Wrap Up

IMS/MTT 2009 in Boston was an extremely successful show for Acceleware.

Acceleware at IMS 2009 in Boston

For our fourth consecutive year, Acceleware will be exhibiting at the International Microwave Symposium (IMS) held in Boston from June 9th through June 11th.  I’m excited to see many familiar faces and to meet many new ones. We will be showcasing our products including our accelerated FDTD software, clustered solutions, and our linear algebra solvers.


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