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    dstack Standard

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    Sold by: dstack 
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    dstack is a streamlined alternative to Kubernetes and Slurm, designed to simplify development and deployment of AI. It works with top cloud providers and on-prem servers.

    Overview

    dstack is a streamlined alternative to Kubernetes and Slurm, specifically designed for AI. It simplifies container orchestration for AI workloads both in the cloud and on-prem, speeding up the development, training, and deployment of AI models.

    dstack is easy to use with any cloud providers as well as on-prem servers.

    dstack supports NVIDIA GPU, AMD GPU, and Google Cloud TPU out of the box.

    Highlights

    • dstack is a streamlined alternative to Kubernetes and Slurm, designed to simplify the development and deployment of AI.
    • It simplifies container orchestration for AI workloads across multiple clouds and on-prem, speeding up the development, training, and deployment of AI models.
    • dstack enables AI teams to work with any tools, frameworks, and hardware across multiple cloud platforms and on-premises.

    Details

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    Delivery method

    Supported services

    Delivery option
    Container image

    Latest version

    Operating system
    Linux

    Deployed on AWS

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    Pricing

    dstack Standard

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    Pricing is based on a fixed subscription cost. You pay the same amount each billing period for unlimited usage of the product. Pricing is prorated, so you're only charged for the number of days you've been subscribed. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Fixed subscription cost

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    $3,000.00/month

    Vendor refund policy

    No refund

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    Usage information

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    Delivery details

    Container image

    Supported services: Learn more 
    • Amazon EKS Anywhere
    • Amazon ECS
    • Amazon EKS
    • Amazon ECS Anywhere
    Container image

    Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.

    Version release notes

    Clusters

    Simplified use of MPI

    startup_order and stop_criteria

    New run configuration properties are introduced:

    • startup_order: any/master-first/workers-first specifies the order in which master and workers jobs are started.
    • stop_criteria: all-done/master-done specifies the criteria when a multi-node run should be considered finished.

    These properties simplify running certain multi-node workloads. For example, MPI requires that workers are up and running when the master runs mpirun, so you'd use startup_order: workers-first. MPI workload can be considered done when the master is done, so you'd use stop_criteria: master-done and dstack won't wait for workers to exit.

    DSTACK_MPI_HOSTFILE

    dstack now automatically creates an MPI hostfile and exposes the DSTACK_MPI_HOSTFILE environment variable with the hostfile path. It can be used directly as mpirun --hostfile $DSTACK_MPI_HOSTFILE.

    CLI

    We've also updated how the CLI displays run and job status. Previously, the CLI displayed the internal status code which was hard to interpret. Now, the the STATUS column in dstack ps and dstack apply displays a status code which is easy to understand why run or job was terminated.

    dstack ps -n 10 NAME BACKEND RESOURCES PRICE STATUS SUBMITTED oom-task no offers yesterday oom-task nebius (eu-north1) cpu=2 mem=8GB disk=100GB $0.0496 exited (127) yesterday oom-task nebius (eu-north1) cpu=2 mem=8GB disk=100GB $0.0496 exited (127) yesterday heavy-wolverine-1 done yesterday replica=0 job=0 aws (us-east-1) cpu=4 mem=16GB disk=100GB T4:16GB:1 $0.526 exited (0) yesterday replica=0 job=1 aws (us-east-1) cpu=4 mem=16GB disk=100GB T4:16GB:1 $0.526 exited (0) yesterday cursor nebius (eu-north1) cpu=2 mem=8GB disk=100GB $0.0496 stopped yesterday cursor nebius (eu-north1) cpu=2 mem=8GB disk=100GB $0.0496 error yesterday cursor nebius (eu-north1) cpu=2 mem=8GB disk=100GB $0.0496 interrupted yesterday cursor nebius (eu-north1) cpu=2 mem=8GB disk=100GB $0.0496 aborted yesterday

    Examples

    Simplified NCCL tests

    With this release improvements, it became much easier to run MPI workloads with dstack. This includes NCCL tests that can now be run using the following configuration:

    type: task name: nccl-tests nodes: 2 startup_order: workers-first stop_criteria: master-done image: dstackai/efa env: - NCCL_DEBUG=INFO commands: - cd /root/nccl-tests/build - | if [ ${DSTACK_NODE_RANK} -eq 0 ]; then mpirun \ --allow-run-as-root --hostfile $DSTACK_MPI_HOSTFILE \ -n ${DSTACK_GPUS_NUM} \ -N ${DSTACK_GPUS_PER_NODE} \ --mca btl_tcp_if_exclude lo,docker0 \ --bind-to none \ ./all_reduce_perf -b 8 -e 8G -f 2 -g 1 else sleep infinity fi resources: gpu: nvidia:4:16GB shm_size: 16GB

    See the updated NCCL tests example  for more details.

    Distributed training

    TRL

    The new TRL example  walks you through how to run distributed fine-tune using TRL , Accelerate  and Deepspeed .

    Axolotl

    The new Axolotl example  walks you through how to run distributed fine-tune using Axolotl   with dstack.

    What's changed

    Full changelog: https://github.com/dstackai/dstack/compare/0.19.11...0.19.12 

    Additional details

    Usage instructions

    Here's the most simple way to run the container image:

    1. Login to the Container Repo Hub
    aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 709825985650.dkr.ecr.us-east-1.amazonaws.com
    1. Pull the container image:
    docker pull 709825985650.dkr.ecr.us-east-1.amazonaws.com/dstack/dstack-enterprise:0.19.12-v1
    1. Run the Container Image
    docker run -it -p 3000:3000 -v $HOME/.dstack-enterprise/server/:/root/.dstack/server 709825985650.dkr.ecr.us-east-1.amazonaws.com/dstack/dstack-enterprise:0.19.12-v1
    1. Click the URL in the container output (e.g., http://localhost:3000  ).

    2. Copy the admin token from the container output to log in to the UI

    For more advanced deployment configurations, check https://dstack.ai/docs/guides/server-deployment/ 

    dstack Standard is fully compatible with the open-source CLI of dstack. More details can be found at dstack documentation: https://dstack.ai/docs/  .

    Support

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    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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