Tesla K40 Hosting

Updated on October 28, 2021

Written by Database Mart

Solve your most demanding High-Performance Computing (HPC) challenges with the Tesla K40 hosting servers. Based on the NVIDIA Kepler™, Tesla GPUs are designed to deliver faster, more efficient compute performance.

Dedicated Tesla K40 Hosting Pricing

Tesla k40 pairs with Eight-Core Xeon E5-2670 and 64GB RAM helping solve your most demanding high-performance computing challenges.

Basic GPU Server

Nvidia Tesla K40

For High-performance computing and large data workloads, such as deep learning and AI reasoning.

GPU:Nvidia Tesla K40

Max GPU: 2

CUDA Cores: 2880

GPU Memory: 12GB

Performance: 4.29 TFLOPS

64 GB RAM

Eight-Core Xeon E5-2670

120GB SSD + 960GB SSD

100Mbps-1Gbps Bandwidth

Supported OS: Windows & Linux

$ 109.00/m

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Purchase a Computer with GPU VS. Rent a GPU Server

Which one suits you better?

Purchasing GPUs

Excellent when equipped with adequate hardware
Expensive
Need extra cost when updating
Once your research or project ends, you may be left with a high-powered machine with nothing to do.
You cannot guarantee that your local computer will be turned on 24 hours a day, nor can you resist an unexpected power outage that may cause your machine to fail.

Renting GPUs

High performance as local GPU Servers
Low Cost
Managed by hosting provider
GPU instance can be turned on or off at any time, and upgrade or downgrade depending on your hardware needs.
99.9% uptime and 24*7 expert hardware monitoring ensure the stable operation of your applications and services, so that your users can have a better experience.

Nvidia Tesla K40 Specifications & Benchmarks

Equipped with 12 GB of memory, the Tesla K40 GPU accelerator is ideal for the most demanding HPC and big data problem sets. It outperforms CPUs by up to 10x2 and includes a Tesla GPUBoost3 feature that enables power headroom to be converted into a user-controlled performance boost. See Tesla K40 gaming Benchmark

Specifications

GPU Microarchitecture Kepler

CUDA Cores 2,880

TDP 230W

Memory Bus Width 384 bit

Memory Clock Speed 3 GHz

Memory Bandwidth 288 GB/s

Memory 12GB GDDR5

System Interface PCI Express Gen 3 x 16

GPU Clock speed 745 MHz

Performance 4.29 TFLOPS

GPU Features in Hosted Tesla K40 Server

Built on the NVIDIA Kepler™ compute architecture and powered by CUDA, Tesla K40 GPU is idea for delivering record acceleration and compute performance efficiency for big data applications.

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

Use the hosted Tesla K40 server to accelerates algorithms such as physics solvers, ray tracing, and sparse matrix multiplication where data addresses are not known beforehand.

Memory Error Protection

The GPU card in the hosted Tesla K40 server 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

Our hosted Tesla K40 server enables the end-user to convert power headroom to higher clocks and achieve even greater acceleration for various HPC workloads.

Flexible Programming Environment with Broad Support of Programming Language and APIs

With the hosted Tesla K40 server, users have the freedom to choose OpenACC, CUDA toolkits for C, C++, or Fortran to express application parallelism and take advantage of the innovative Kepler architecture