Kubernetes based
GPU cloud

  • More cost effective Nvidia RTX 2080 Ti
  • Fast data storage based on NVMe SSD
  • First load data via SSH, then rent a GPU
    • up to 3x cheaper per FLOPS
    than AWS or Google Cloud
    Located in Sweden

    Templates with popular machine learning tools

    tensorflow logopytorch logokeras logocaffe logocaffe2 logomxnet logoonnx logojupyter logoh2o.ai logofast.ai logo

    Nvidia RTX 2080 Ti

    the best choice for deep learning in cloud

    CardPrice per hour2FP32, TFLOPS (peak)FP32 (ML benchmarks score)1Memory, GBTensor coresCUDA cores
    2080Ti

    by Puzl

    		0.29€14.21
    11

    GDDR6

    		5444352
    Tesla T4
    0.31€

    x1.07

    8.1

    x0.57

    0.53

    16

    GDDR6

    320

    x0.59

    2560

    x0.59

    Tesla V100
    1.26€

    x4.34

    15.7

    x1.11

    1.57

    16

    HBM2

    640

    x1.18

    5120

    x1.18

    1. Based on average normalized GPU score for ResNet, Inception and AlexNet benchmarks. Normalization was performed to 2080Ti score (1 is 2080 Ti score).

    2. The minimum market price per 1 GPU on demand, taken from public price lists of popular cloud and hosting providers. Information is current as of June 2020.

    * Benchmarks are made on instances with 1 GPU, 16GB RAM, 4vCPU and fast storage with similar IOPS and bandwidth rate.

    ** All multiplicators are calculated in proportion to 2080Ti.

    Running on professional server platforms
    with last generation AMD EPYC™

    amd epyc cpu
    AMD EPYC™ 7502 3.3GHz

    *AMD, and the AMD Arrow logo, AMD EPYC and combinations thereof are trademarks of Advanced Micro Devices, Inc.

    AMD EPYC™ CPU

    With 2nd generation AMD processors you can allocate 64 vCPU and 10 GPU in one Docker container.

    Flexible NVMe storage

    Fast, reliable storage for your datasets and trained models, runtime-extensible up to 4TB.

    Fast ECC RAM

    DDR4 ECC 2.9Ghz memory with flexible allocation up to 384GB.

    Zero infrastructure

    Instant
    start
    Launch your code in seconds with no cloud instances management
    Kubernetes
    out of the box
    You get full access to a separate Kubernetes namespace, pre-configured with all security poliicies needed
    Fair
    costs
    Pay only for resources used by your running application, with no cluster maintenance fee
    kube-console-example

    Easy to deploy

    No need to explore one more cloud API:
    Kubernetes is a new unified way to deploy your applications.
    kubernetes dashboard
    puzl dashboard

    Configurator

    Docker container configuration

    GPU
    0.29€ per hour
    RAM
    0.002€
    CPU
    0.015€
    Docker Image
    0.007€ per GB*day

    Disk space will be provided to store Docker image files for containers of your pod.

    NVMe-based storage
    0.004€ per GB*day

    Fast flexible storage for your datasets. To reduce your costs you can load data via SSH first and run pod with GPUs after.

    Container File System

    A container file system provides a temporary fast storage for each container in your pod. Its capacity cannot be changed. You pay only if your application use it.

    Capacity: 5 GB
    Price: 0.007€ per GB*day for used container file system

    *1GB = 1024MB

    My pod

    1 x NVIDIA 2080Ti
    0.29€ per hour
    8 GB RAM
    0.016€ per hour
    2 vCPU
    0.03€ per hour
    Docker Image, 1GB
    0.007€
    Container File System, 5GB
    0.007€ per used GB*day
    Resources cost per hour
    0.33629€
    Resources cost per month
    245.49€

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    © GPU Computing OÜ, 2020

    Harju maakond, Tallinn, Kesklinna linnaosa, Tartu mnt 83-701, 10115 Estonia

    Company code 14476114

    VAT number EE102212851