Computing Hardware

The CRC provides different hardware types to target different computing use cases. These hardware profiles are grouped together under a common cluster name and are further divided into partitions to highlight differences in the architecture or usage modes.

Cluster Acronym Full Form of Acronym Description of Use Cases
mpi Message Passing Interface For tightly coupled parallel codes that use the Message Passing Interface APIs for distributing computation across multiple nodes, each with its own memory space
htc High Throughput Computing For genomics and other health sciences-related workflows that can run on a single node
smp Shared Memory Processing For jobs that can run on a single node where the CPU cores share a common memory space
gpu Graphics Processing Unit For AI/ML applications and physics-based simulation codes that had been written to take advantage of accelerated computing on GPU cores

 

 

Below, you will find the hardware specifications for each cluster and the partitions that compose it: 

MPI Cluster

The MPI nodes are for tightly-coupled codes that are parallelized using the Message Passing Interface (MPI) and benefit from low-latency communication through an Infiniband (HDR200) or Omni-Path (OPA) network. Your job must request a minimum of 2 nodes.

Partition Architecture Nodes Cores/Node Mem/Node Mem/Core Scratch Network Nodes
mpi Intel Xeon Gold 6342 (Ice Lake) 136 48 512 GB 10.6 GB 1.6 TB NVMe HDR200; 10GbE mpi-n[0-135]
opa-high-mem Intel Xeon Gold 6132 (Skylake) 36 28 192 GB 6.8 GB 500 TB SSD OPA; 10GbE opa-n[96-131]

 

HTC Cluster

These nodes are designed for High Throughput Computing workflows such as gene sequence analysis, neuroimaging data processing, and other data-intensive analytics.

Partition Architecture --constraint Nodes Cores/Node Mem/Node Mem/Core Scratch Network Nodes
htc AMD EPYC 9374F (Genoa) amd, genoa 20 64 768 GB 12 GB 3.2 TB NVMe 10GbE htc-n[50-69]
Intel Xeon Platinum 8352Y (Ice Lake) intel, ice_lake 18 64 512 GB 8 GB 2 TB NVMe 10GbE htc-n[32-49]
Intel Xeon Platinum 8352Y (Ice Lake) intel, ice_lake 4 64 1 TB 16 GB 2 TB NVMe 10GbE htc-1024-n[0-3]
Intel Xeon Gold 6248R (Cascade Lake) intel, cascade_lake 8 48 768 GB 16 GB 960 GB SSD 10GbE htc-n[24-31]

 

SMP Cluster

The SMP nodes are appropriate for programs that are parallelized using the shared memory framework. These nodes are similar to your laptop but with more memory and more CPU cores. To request a particular feature (such as an Intel host CPU), add the following directive to your job script:

 #SBATCH --constraint=intel

Multiple features can be requested by providing a comma-separated list (without intervening spaces):

 #SBATCH --constraint=amd,genoa

 

Partition Architecture --constraint Nodes Cores/Node Mem/Node Mem/Core Scratch Network Nodes
smp AMD EPYC 9374F (Genoa) amd, genoa 43 64 768 GB 12 GB 3.2 TB NVMe 10GbE smp-n[214-256]
AMD EPYC 7302 (Rome) amd, rome 55 32 256 GB 8 GB 1 TB SSD 10GbE smp-n[156-210]
Retired  Intel Xeon Gold 6126 (Skylake) intel, skylake 132 24 192 GB 8 GB 500 TB SSD 10GbE smp-n[24-113,115-122,126-155]
high-mem Intel Xeon Platinum 8352Y (Ice Lake) intel, ice_lake 8 64 1 TB 16 GB 10 TB NVMe 10GbE smp-1024-n[1-8]
Intel Xeon Platinum 8352Y (Ice Lake) intel, ice_lake 2 64 2 TB 32 GB 10 TB NVMe 10GbE smp-2048-n[0-1]
AMD EPYC 7351 (Naples) amd, naples 1 32 1 TB 32 GB 1 TB NVMe 10GbE smp-1024-n0
Intel Xeon E7-8870v4 (Broadwell) intel, broadwell 4 80 3 TB 38 GB 5 TB SSD 10GbE smp-3072-n[0-3]

 

GPU Cluster

The GPU nodes are targeted for applications specifically written to take advantage of the inherent parallelism and massive amounts of cores in the architecture. We name the partitions after the GPU type along with a suffix as needed to indicate usage mode. The partition parameters are described below.

  • Partition: l40s. This partition is appropriate for AI, simulations, 3D modeling workloads that require up to 4x gpus on a single node and rely on single or mixed precision operations (Note: This partition does not support double precision - FP64).
  • Partition: a100. This is the default partition in the gpu cluster and is appropriate for workflows that require up to 4x gpus on a single node. To request a particular feature (such as an Intel host CPU), add the following directive to your job script:

 #SBATCH --constraint=intel

Multiple features can be specified in a comma-separated string.

  • Partition: a100_multi. This partition supports multi-node GPU workflows. Your job must request a minimum of 2 nodes and 4 GPUs on each node.
  • Partition: a100_nvlink. This partition supports multi-GPU computation on an Nvidia HGX platform with 8x A100 that are tightly coupled through an NVLink switch. To request a particular feature (such as an A100 with 80GB of GPU memory), add the the following directive to your job script: 

#SBATCH --constraint=80g

  • Partition: gtx1080. Older gaming GPUs with 11GB of memory
  • Partition: v100. Tesla V100 GPUs with 32GB of HBM2 memory
  • Partition: power9. Four nodes of IBM Power System AC922: dual-socket Power9 (16C, 2.7GHz base, 3.3GHz turbo) with a direct NVLink to 4x V100 GPUs. Code must be compiled for the Power9 platform in order to work.

 

Partition Nodes GPU Type GPU/Node --constraint Host Architecture Core/Node Max Core/GPU Mem/Node Mem/Core Scratch Network Nodes
l40s 20 L40S 48GB 4 l40s,48g,intel Intel Xeon Platinum 8462Y+ 64 16 512 GB 8 GB 7 TB NVMe 10GbE gpu-n[55-74]
a100 10 A100 40GB PCIe 4 a100,40g,amd AMD EPYC 7742 (Rome) 64 16 512 GB 8 GB 2 TB NVMe HDR200; 10GbE gpu-n[35-44]
2 A100 40GB PCIe 4 a100,40g,intel Intel Xeon Gold 5220R (Cascade Lake) 48 12 384 GB 8 GB 1 TB NVMe 10GbE gpu-n[33-34]
a100_multi 10 A100 40GB PCIe 4 a100,40g,amd AMD EPYC 7742 (Rome) 64 16 512 GB 8 GB 2 TB NVMe HDR200; 10GbE gpu-n[45-54]
a100_nvlink 2 A100 80GB SXM 8 a100,80g,amd AMD EPYC 7742 (Rome) 128 16 1 TB 8 GB 2 TB NVMe HDR200; 10GbE gpu-n[31-32]
3 A100 40GB SXM 8 a100,40g,amd AMD EPYC 7742 (Rome) 128 16 1 TB 8 GB 12 TB NVMe HDR200; 10GbE gpu-n[28-30]
gtx1080 9 GTX 1080 Ti 11GB 4   Intel Xeon Silver 4112 (Skylake) 8 2 96 GB 12 GB 480 GB SSD 10GbE gpu-n[17-25]
power9 4 V100 32GB SXM 4   IBM Power System AC922 128 threads 16 512 GB 4 GB 1 TB SSD HDR100; 10GbE ppc-n[0-4]

 

Portal: Viz Nodes

Users should open the Web URL in a browser to access a Linux Desktop. The Web URL will resolve to a backend hostname in a round-robin fashion to help balance usage.

Web URL backend hostname GPU Type # GPUs Host Architecture Cores Mem Mem/Core Scratch Network
https://viz.crc.pitt.edu viz-n0.crc.pitt.edu GTX 1080 8GB 2 Intel Xeon E5-2680v4 (Broadwell) 28 256 GB 9.1 GB 1.6 TB SSD 10GbE
viz-n1.crc.pitt.edu RTX 2080 Ti 11GB 2 Intel Xeon Gold 6226 (Cascade Lake) 24 192 GB 8 GB 1.9 TB SSD 10GbE

 

Portal: Login Nodes

Users should use the hostname as the remote host target of an ssh session. The hostname will resolve to a backend hostname in a round-robin fashion to help balance usage. 

hostname backend hostname Architecture Cores/Node Mem Mem/Core OS Drive Network
h2p.crc.pitt.edu login0.crc.pitt.edu Intel Xeon Gold 6326 (Ice Lake) 32 256 GB 8 GB 2x 480 GB NVMe (RAID 1) 25GbE
login1.crc.pitt.edu Intel Xeon Gold 6326 (Ice Lake) 32 256 GB 8 GB 2x 480 GB NVMe (RAID 1) 25GbE
htc.crc.pitt.edu login3.crc.pitt.edu Intel Xeon Gold 6326 (Ice Lake) 32 256 GB 8 GB 2x 480 GB NVMe (RAID 1) 25GbE