Overview
Phoenix is a heterogeneous supercomputer. Heterogeneous supercomputers feature processors and interconnects that are of different types, brands, and architectures. This can complicate system management and optimization but offers a wider range of available hardware. This page describes the publicly available hardware within Phoenix for reference
Node Type | CPU | Memory | Accelerator |
---|---|---|---|
Standard Compute | 28 Cores (2x Intel Broadwell) | 128 GiB | N/A |
High Memory | 56 Cores (2x Intel Skylake Xeon Gold 6132 @ 2.6GHz) | 1500 GiB | N/A |
GPU V100 | 40 Cores (2x Intel Skylake Xeon Gold 6148 @ 2.40GHz) | 360 GiB | 4x NVIDIA V100 32GiB |
Intel Phi | 256 Cores (2x Intel Knights Landing Phi) | 128 GiB | N/A |
There is privately owned hardware that has very different specs. See the Phx Status Page for the full features of every node
Requesting Resources
Requesting CPUs
To request a given number of CPUs sharing the same node, you can use the following in your SBATCH
:
#SBATCH -N 1 # Number of Nodes #SBATCH -c 5 #Number of Cores per task or interactive -N 1 -c 5
This will create a job with 5 CPU cores on one node.
To request a given number of CPUs spread across multiple nodes, you can use the following:
#SBATCH -N 2-4 # number of nodes to allow tasks to spread across (MIN & MAX) #SBATCH -n 10 # number of TASKS #SBATCH -c 5 # CPUs per TASK or interactive -N 2-4 -n 10 -c 5
The above example will allocate a total of 50 cores spread across as few as 2 nodes or as many as 4 nodes.
Take note of the inclusion or omission of -N
:
#SBATCH -c 5 # CPUs per TASK #SBATCH -n 10 # number of TASKS or interactive -n 10 -c 5
This reduced example will still allocate 50 cores, 5 cores per task on any number of available nodes. Note, that unless you are using MPI-aware software, you will likely prefer to always add -N
, to ensure that each job worker has sufficient connectivity.
The -c
and -n
flags have similar effects in Slurm in allocating cores, but -n
is the number of tasks, and -c
is the number of cores per task. MPI processes bind to a task, so the general rule of thumb is for MPI jobs to allocate tasks, while serial jobs allocate cores, and hybrid jobs allocate both.
See the official Slurm documentation for more information: https://slurm.schedmd.com/sbatch.html
Requesting Memory
Cores and memory are de-coupled: if you need only a single CPU core but ample memory, you can do so like this:
#SBATCH -c 1 #SBATCH -N 1 #SBATCH --mem=120G or interactive -N 1 -c 1 --mem=120G
If you do not specify --mem
, you will be allocated 2GiB per CPU core OR 24GiB per GPU by default.
To request more than 512GiB of memory, you will need to use the highmem partition
#SBATCH -p highmem #SBATCH --mem=1400G
To request all available memory on a node:
This will allocate all CPU cores memory (up to 2TiB depending on the node) to your job. This will prevent any other jobs from landing on this node. Only use this if you truly need that much memory
#SBATCH --exclusive #SBATCH --mem=0
Requesting GPUs
To request a GPU, you can specify the -G
option within your job request:
This will allocate the first available GPU that fits your job request
#SBATCH -G 1 or interactive -G 1
To request multiple GPU’s specify a number greater than 1:
#SBATCH -G 4 or interactive -G 4
To request a specific number of GPU’s per node when running multi node:
#SBATCH -N 2 # Request two nodes #SBATCH --gpus-per-node=2 #Four total GPUs, two per node
To request a specific type of GPU (a100 for example):
#SBATCH-G a100:1 or interactive -G a100:1
Additional Help
If you require further assistance on this topic, please contact the Research Computing Team. To create a support ticket review our RTO Request Help page. For quick inquiries, reach out via our #rc-support Slack Channel or attend our office hours for live assistance. We also offer a series of Educational Opportunities and Workshops.