Tesla Accelerated Computing Platform

The Kepler-based Tesla family of GPUs is part of the innovative Tesla Accelerated Computing Platform. As the leading platform for accelerating data analytics and scientific computing, it combines the world’s fastest GPU accelerators, the widely used CUDA parallel computing model, and a comprehensive ecosystem of software developers, software vendors, and datacenter system OEMs.

Tesla K80 GPU Accelerator

This accelerator is designed for the most demanding computational tasks, combining 24 GB of memory with blazing-fast memory bandwidth and leading compute performance for single and double-precision workloads. Equipped with the latest NVIDIA GPU Boost™ technology, the Tesla K80 intelligently monitors GPU usage to maximize throughput1 and outperforms CPUs by up to 10x2.

Hosted Nvidia Tesla K80 GPU

Device Type
Graphics Cards
GPU Model
Nvidia Tesla K80
Performance
8.73 TFLOPS
Graphics Ram
24GB GDDR5
Graphics Card Interface
PCI-E
Hardware Interface
PCIE x 10
Graphics Coprocessor
Nvidia Tesla
Item Dimensions
17.6 x 7.8 x 4.2 inches
CUDA Cores
4992
Graphics Ram Size
24 GB
GPU Processing Power
8776
Memory Bus Width
2 X 384-bit
Memory Clock Speed
5000 MHz

Server Hardware Resources

If choosing an appropriate GPU is critical, it's equally essential for your business to select proper server hardware resources based on the number of users.
Professional GPU Server
Nvidia Tesla K80
20% OFF
AI, Machine Learning
128 GB RAM
8 Cores Xeon E5-2689
120GB SSD + 960GB SSD
100Mbps Unmetered Bandwidth
$ 159.00/m
$ 127.20/m

Nvidia Tesla K80 GPU Features

Dynamic Parallelism

Enables GPU threads to automatically spawn new threads. By adapting to the data without going back to the GPU, this greatly simplifies parallel programming.

Hyper-Q

Allows multiple CPU cores to simultaneously use the CUDA cores on a single or multiple Kepler-based GPUs. This dramatically increases GPU utilization, simplifies programming, and slashes CPU idle times.

System Monitoring

Integrates the GPU subsystem with the host system’s monitoring and management capabilities, such as IPMI or OEM-proprietary tools. IT staff can now manage the GPU processors in the computing system using widely used cluster/grid management solutions.

L1 and L2 Caches

Accelerates algorithms such as physics solvers, ray tracing, and sparse matrix multiplication where data addresses are not known beforehand.

Memory Error Protection

Meets a critical requirement for computing accuracy and reliability in data centers and supercomputing centers. Both external and internal memories are ECC protected in the Tesla K80 and K40.

Asynchronous Transfer with Dual DMA Engines

Turbocharges system performance by transferring data over the PCIe bus while the computing cores are crunching other data.

GPU Boost

Enables the end-user to convert power headroom to higher clocks and achieve even greater acceleration for various HPC workloads.

Dynamically Scales GPU Clocks

Dynamically scales GPU clocks for maximum application performance and improved energy efficiency.

Flexible Programming Environment with Broad Support of Programming Language and APIs

Offers the freedom to choose OpenACC, CUDA toolkits for C, C++, or Fortran to express application parallelism and take advantage of the innovative Kepler architecture.

2x Shared Memory and 2x Register File

Increases effective throughput and bandwidth with 2x shared memory and 2x register file compared to the K40.

Zero-power Idle

Increases data center energy efficiency by powering down idle GPUs when running legacy nonaccelerated workloads.

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