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What is ALICE

 

ALICE (Academic Leiden Interdisciplinary Cluster Environment) is the high-performance computing (HPC) facility of the partnership between Leiden University and Leiden University Medical Center (LUMC). It is available to any researcher from both partners. Leiden University and LUMC aim to help deliver cutting edge research using innovative technology within the broad area of data-centric HPC. Both partners are responsible for the hosting, system support, scientific support and service delivery of several large super-computing and research data storage resources for the Leiden research community.

ALICE is one of the projects to provide research IT infrastructure and support centrally for Leiden University. If you want know more about other projects, please have a look at the confluence space of the RICC team: RICC

• 1 What is ALICE
• 2 Why ALICE
• 3 Overview of the cluster
• 4 Future plans
• 5 Costs overview
• 6 Hardware Description
  • 6.1 List of Nodes
  • 6.2 GPU overview

Why ALICE

High-Performance Computing (HPC) previously the domain of theoretical scientists and computer and software developers is becoming ever more important as a research tool in many research areas. An HPC facility, providing serious computational capabilities, combined with easy and flexible local access, is a strong advantage for these research areas. ALICE is the HPC facility that answers those needs for Leiden University (LU) and Leiden University Medical Center (LUMC). It is available to all researchers and students from both LU and LUMC.

The ALICE facility currently implemented is a first phase edition of what will be a larger Hybrid HPC facility for research, exceeding the capabilities of what individual institutes can build and will provide a stepping stone to the larger national facilities.

The facility aims to be an easily accessible, easily usable system with extensive local support at all levels of expertise. Given the expected diverse use, diversity is implemented in all aspects of computing, namely: the number of CPU's, GPU's and the ratio of these two numbers; the size of the core memory to the CPU's; the data storage size and location; and the speed of the network.

ALICE provides not only a sophisticated production machine but is also a tool for educating all aspects of HPC and a learning machine for young researchers to prepare themselves for national and international HPC.

Overview of the cluster

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Conceptual View of ALICE

The ALICE cluster is a hybrid cluster consisting of

• 2 login nodes (4 TFlops)

• 20 CPU nodes (40 TFlops)

• 24 GPU nodes (68 GPU, 104 TFlops CPU + 1082 TFlops GPU)

• 1 High Memory CPU node (4 TFlops)

• Storage Devices (local storage + home + shared-scratch): 45 x 15TB + 70TB + 364TB = 1109 TB)

In summary: 1234 TFlops, 1712 cores (3424 threads), 17.9 TB RAM.

In addition several research groups have also dedicated hardware within ALICE that is not listed above.

You can find a more comprehensive description of the individual components of ALICE in the section Hardware description.

ALICE is a pre-configuration system for the university to gain experience with managing, supporting and operating a university-wide HPC system. Once the system and governance have proven to be a functional research asset, it will be extended and continued for the coming years.

Future plans

Apart from our own expansion plans, we are always open to collaborate with other groups/institutes on expanding and improving ALICE.

The expansion that are currently planned include:

• Additional CPU, high-memory and GPU nodes (estimated Q2 2025)

• Switch from IB to 100GbE ethernet network (estimated end of Q1 2025)

• Increase the storage capacity (Q1 2025)

In addition, we have the following major changes planned

Costs overview

The ALICE cluster is a shared facility owned by the participating groups and the University. Currently, access to the ALICE cluster and related services is provided free of charge to all researchers and students at LU and LUMC.

Hardware Description

List of Nodes

GPU overview

The table below lists the types of GPUs available on the GPU-equipped nodes.