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Promotion - 50% off sale (Normally £1,737.29)
With 448 application-acceleration cores per board, Tesla processors offload parallel computations from the CPU to dramatically accelerate the floating point calculation performance.
In conjunction with PNY, Boston and NVIDIA have launched an exclusive Tesla discount scheme, whereby all Academic and Educational institutions can receive 10% off the NVIDIA C2075 Tesla! If you are an Academic institution and would like to find out more about this great offer, please click here.
With 448 application-acceleration cores per board, Tesla processors offload parallel computations from the CPU to dramatically accelerate the floating point calculation performance. By adding a Tesla processor, engineers, designers, and content creation professionals accelerate some of the most complex tools exponentially faster than by adding a second CPU. It’s an unbeatable solution for getting more done in less time.
Take advantage of the newest analysis, simulation, and rendering tools within industry-leading applications and see results in as little as half the time. Tesla C2075 companion processors deliver parallel processing power right at the desk, capable of streamlining the way users work every day. This means you can now explore, discover and deliver higher-quality projects faster than you ever thought possible.
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Card Form Factor
9.75"
Core Clock Speed
1.15 GHz
Double Precision Floating Point Performance
515 Gflops
GPU Family
NVIDIA Tesla Series
GPU Manufacturer
NVIDIA
GPU Model
Tesla C2075
Interface
PCI-E x16
Manufacturer
Supermicro
Max Resolution
1600 x 1200
Memory Bandwidth
144 GB/sec
Memory Interface
384-bit
Memory Sizes
6GB
Memory Speed
1.5GHz
Memory Type
GDDR5
Number of Cores
448
Other Features
Thermal Solution: Active Fansink
Power Consumption
225W
Single Precision Floating Point Performance
1.03 Tflops
To help our clients make informed decisions about new technologies, we have opened up our research & development facilities and actively encourage customers to try the latest platforms using their own tools and if necessary together with their existing hardware. Remote access is also available
The annual GPU Technology Conference is returning once again in San Jose, California. See what awaits you!