Alpine Quick Start

Alpine is the University of Colorado Boulder Research Computing’s third-generation high performance computing (HPC) cluster. Alpine is a heterogeneous compute cluster currently composed of hardware provided from University of Colorado Boulder. Additional contributions provided from Colorado State University and Anschutz Medical Campus are planned for the near future. Alpine currently offers 204 compute nodes and a total of 12,992 cores.

Alpine can be securely accessed anywhere, anytime using OpenOnDemand or ssh connectivity to the CURC system.

Alpine Quick-Start

  1. From a login node load the slurm/alpine module to access the SLURM job scheduler instance for Alpine:

    $ module load slurm/alpine

  2. Once the Alpine Slurm job scheduler has been loaded you can submit and start jobs on the Alpine cluster. Consult the requesting resources section and the examples section below to learn how to direct your jobs to the appropriate Alpine compute nodes.

  3. Software can be loaded into the Alpine compute environment via the LMOD module system, which allows users choose software from our pre-installed software stack.

  4. If you would like to use software that is not within our preinstalled stack your application must be compiled using acompile (similar to ssh’ing to an scompile node on Summit). More information about the acompile function can be found under our partitions section.

Consult our compiling and linking documentation for more information on compiling software. You can also submit a software request using our Software Request Form.

Cluster Summary

Nodes

The Alpine cluster is made up of different types of nodes outlined below:

  • CPU nodes: 188 AMD Milan Compute nodes (184 nodes with 64 cores/node, 4 nodes with 48 cores/node)
  • GPU nodes:
    • 8 GPU-enabled (3x AMD MI100) atop AMD Milan CPU
    • 8 GPU-enabled (3x NVIDIA A100) atop AMD Milan CPU
For a full list of nodes on Alpine use the command: scontrol show nodes. Get single node details with the scontrol show nodes <node name> command.

Interconnect

The Alpine cluster has different types of interconnects/fabrics which connect different types of hardware, outlined below:

  • CPU nodes: HDR-100 InfiniBand (200Gb inter-node fabric); InfiniBand in progress as of September 2022
  • GPU nodes: 2x25 Gb Ethernet +RoCE
  • Scratch Storage: 25Gb Ethernet +RoCE

Node Features

The Alpine cluster features some heterogeneity. A variety of feature tags are applied to nodes deployed in Alpine to allow jobs to target specific CPU, GPU, network, and storage requirements.

Use the sinfo command to determine the features that are available on any node in the cluster.

Note: Feature descriptions and finalized partitions names are still being added to Alpine nodes. Refer to the description of features list below for current node features.
sinfo --format="%N | %f"

Description of features

  • Milan: 64-core and dual-socket 32-core AMD Milan EPYC CPU
  • A100: NVIDIA A100 GPU
  • MI100: AMD MI100 GPU- localraid: large, fast RAID disk storage in node
  • rhel8: RedHat Enterprise Linux version 8 operating system

Job Scheduling

All jobs on Alpine are run through a queue system using the SLURM job scheduler. Though many HPC workflows are run through batch-type jobs, interactive jobs on compute nodes are allowed but these must also be initiated through the scheduler. High-priority jobs move to the top of the queue and are thus guaranteed to start running within a few minutes, unless other high-priority jobs are already queued or running ahead of them. High-priority jobs can run for a maximum wall time of 24 hours. Low-priority jobs have a maximum wall time of 7 days.

More details about how to use SLURM to run jobs can be found in our running applications with jobs documentation.

Allocations

All new Alpine users are granted an initial allocation (account) called ucb-general. Users who require more core hours than ucb-general can provide are advised to apply for an allocation. The allocation process requires that users have run example jobs in ucb-general that can be assessed by RC for efficiency/optimation on Alpine. Research Computing will then work with users to make workflows more efficient if needed and then grant the allocation.

You can read more about the allocation process and why you might choose to apply for one on our Allocation’s page.

Alpine is jointly funded by the University of Colorado Boulder, the University of Colorado Anschutz, Colorado State University, and the National Science Foundation (award 2201538).

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