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
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 being discussed include:
Additional CPU, high-memory and GPU nodes (estimated end of Q2 2024)
Infiniband 100GbE network on all nodes (estimated end of Q2 2024Q1 2025)
In addition, we have the following major changes planned
Migration of ALICE to new operating system (estimated end of Q1 2024)
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
Node Name | CPU | Cores | Memory | Local scratch | GPUs per node | Infiniband | Public Access | Purpose | Type |
---|---|---|---|---|---|---|---|---|---|
nodelogin0[1-2] | 24 | 384 GB | 15 TB | 1 |
| Login nodes | |||
node0[01-20] | 24 | 384 GB | 15 TB | 0 |
| CPU Node | |||
node021 | 32 | 768 GB | 11 TB | 0 |
| CPU Node | Supermicro SC116AC2-R706WB2 | ||
node0[22-24] | 64 | 256 GB | 5 TB | 0 | CPU Node | Supermicro AS -1115CS-TNR | |||
node801 | 24 | 2048 GB | 20 TB | 0 |
| High-Memory Node | |||
node802 | 128 | 4096 GB | 19 TB | 0 | (Partially) | High-Memory Node | Supermicro SERVERline Individual | ||
node8[51-60] | 24 | 384 GB | 15 TB | 4 |
| GPU Node | |||
node86[1-2] | 48 | 64GB | 15T | 1 |
| GPU Node | DellEMC PowerEdge R7515 | ||
node8[63-64] | 64 | 256GB | 15T | 2 |
| GPU Node | Gigabyte R282-Z93 | ||
node8[65-76] | 64 | 256GB | 15T | 4 (MIG) |
| GPU Node | Gigabyte R282-Z93 |
GPU overview
The table below lists the types of GPUs available on the GPU-equipped nodes.
Hostname | Public Access | GPU type | Memory | Shader cores | Tensore Cores | CUDA Compute Capability |
---|---|---|---|---|---|---|
nodelogin0[1-2] |
| Tesla T4 | 16 GB | 2560 | 320 | 7.5 |
node8[51-60] |
| 4 x PNY GeForce RTX 2080TI | 11 GB | 4352 | 544 | 7.5 |
node86[1-2] |
| Tesla T4 | 16GB | 2560 | 320 | 7.5 |
node8[63-64], node8[75-76] |
| A100 | 80GB | 6912 | 432 | 8.0 |
node8[65-74] | 2 x A100 MIG 4g.40GB | 40GB | 3949 | 246 | 8.0 | |
node8[65-74] | 2 x A100 MIG 3g40gb | 40GB | 2962 | 185 | 8.0 |