PNY 24GB NVIDIA Tesla K80 Passively Cooled Accelerator Module

PNY NVIDIA Tesla K80 Accelerator, 4992 CUDA Cores, 24GB GDDR5 (12GB Per GPU), 384 Bit, PCI-E 3.0 x16, Passively Cooled

PNY
Scan code: LN61554 Manufacturer code: TCSK80M-PB Request call
£4,962.49
In stock
Pay on Scan Finance with a 10% deposit from just £123.94 / month (APR 15.9%)
3xs Approved High End
Delivery options £11.50 By DPD On 12th Dec 2016 DPD Delivered to your specified address. Receive SMS with one-hour delivery window. Free Collect Instore Q-Collect Place your order online and collect from our Bolton store with Q-Collect. Weekend, timed and European delivery options are available at checkout
Product Overview Accelerate your most demanding single and double precision workloads in scientific computing, seismic processing, and data analytics applications by upgrading to the NVIDIA Tesla K80 dual-GPU accelerator.
The Tesla K80 accelerator delivers more than 2x application speed-up compared to the previous generation of accelerators, and up to 10x faster performance compared to CPUs. With exclusive features like 24 GB of GDDR5 memory, 480 GB/s memory bandwidth, and improved GPU Boost technology, the Tesla K80 delivers the computational horsepower that allows you to crunch through petabytes of data and run simulations faster than ever before.

PNY provides unsurpassed service and commitment to its professional graphics customers offering: 3 year warranty, pre- and post-sales support, dedicated Quadro Field Application engineers and direct tech support hot lines. Features • 4992 CUDA Cores.
• Core Clock: 560Mhz, Boost Clock: 562-875MHz
• 24GB GDDR5 (12GB per GPU) Memory.
• Peak single precision floating point performance: 8.74 Tflops (GPU Boost Clocks), 5.6 Tflops (Base Clocks)
• Suitable for Windows and Linux servers.
Specifications
Specifications
Graphics Chipset Tesla
Edition K80
Microarchitecture Kepler
GPU Name  
NVIDIA CUDA Cores 4992
Memory Size 24 (12 per GPU) GB
Memory Bit Rate 384 Bit
Memory Bandwidth 240 per GPU GB/s
Memory Type GDDR5
ECC Technology No
Single Precision Processing Yes
Single Precision Performance  
Double Precision Processing Yes
Double Precision Performance  
Integer Operations (INT8)  
Concurent Users N/A
H.264 1080p30 Streams N/A
Cooling Passive
Graphics Interface PCIe (x16)
Graphics Output  
Maximum Digital Resolution  
Maximum VGA Resolution  
SLi  
Multi Monitor  
HDCP Ready No
Supported Compute APIs  
Supported Graphics APIs  
Microsoft DirectX Support  
Form Factor Dual Slot
Low Profile Compatible No
Low Profile Support N/A
Board Power 300 W
Graphics Card Power Connectors 1 x 8-pin PCIe
Minimum Recommended PSU  
Maximum GPU Temperature  
Dimensions 111.150 (H) × 267 (L) mm
Package Type  
Warranty

Please note your statutory rights are not affected.

For further information regarding Scan's warranty procedure please see our terms and conditions

Details
Duration:
36 months
Type:
Return to base
DOA Period:
28 days
RTB Period:
120 months
Manufacturer Contact Details
Manufacturer:
PNY/SCAN
Telephone:
0871 472 4747
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Date Issued: 2nd Dec 2010

NVIDIA® CUDA parallel computing architecture is enabled on GeForce, Quadro, and Tesla products. Whereas GeForce and Quadro are designed for consumer graphics and professional visualization respectively, the NVIDIA® Tesla™ product family is designed ground-up for parallel computing and offers exclusive computing features.

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Date Issued: 22nd Oct 2008

CUDA technology is the world’s only C language environment that enables programmers and developers to write software to solve complex computational problems in a fraction of the time by tapping into the many-core parallel processing power of GPUs.

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Explaining how a modern GPU works in completeness would take a book. Or two. Per class of chip. Per vendor. They’re extraordinarily complex pieces of engineering and production, and the end result contains more transistors than multiple modern x86 processors.

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Reviews
Questions & Answers
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PNY 24GB NVIDIA Tesla K80 Passively Cooled Accelerator Module
PNY 24GB NVIDIA Tesla K80 Passively Cooled Accelerator Module