Mind Cluster Nodes

The MIND Cluster is a heterogeneous high-performance computing environment supporting computational neuroscience, neuroimaging, artificial intelligence, and data-intensive research. It includes CPU-only and GPU-accelerated compute nodes spanning multiple hardware generations. All nodes are managed via SLURM and connected through a 100 Gbps InfiniBand network.

Cluster Overview
  • Total compute nodes: 14
  • GPU-enabled nodes: 11
  • CPU-only nodes: 3
  • Total logical CPU cores: 1,056
  • Total system memory: 7.38 TB
  • Total GPUs: 64
Node Specification Table
Node CPU Model CPU Year Logical Cores RAM (GB) GPU Model GPU Count GPU Memory (GB) GPU Year Architecture
mind-0-15 AMD EPYC 7443 2021 96 1007.4 None 0 CPU-only
mind-0-16 AMD EPYC 7443 2021 96 1007.4 None 0 CPU-only
mind-0-17 AMD EPYC 7443 2021 96 1007.4 None 0 CPU-only
mind-0-18 Intel Xeon E5-2620 v4 2016 32 125.6 RTX 2080 Ti 4 11 2018 Turing
mind-0-20 Intel Xeon E5-2620 v4 2016 32 125.6 RTX 2080 Ti 4 11 2018 Turing
mind-0-22 Intel Xeon E5-2620 v4 2016 32 125.6 RTX 2080 Ti 4 11 2018 Turing
mind-0-24 Intel Xeon E5-2620 v4 2016 32 125.6 RTX 2080 Ti 4 11 2018 Turing
mind-0-26 Intel Xeon Silver 4208 2019 32 125.3 RTX 3090 2 24 2020 Ampere
mind-0-28 Intel Xeon Silver 4310 2021 48 250.6 RTX A5000 4 24 2021 Ampere
mind-1-11 Intel Xeon E5-2620 v4 2016 32 125.6 TITAN Xp 4 12 2017 Pascal
mind-1-15 AMD EPYC 7513 2021 128 1007.7 L40S 8 48 2023 Ada Lovelace
mind-1-19 AMD EPYC 9554 2022 128 1133.4 RTX PRO 6000 10 96 2025 Blackwell
mind-1-24 Intel Xeon E5-2687W v4 2016 48 251.7 TITAN RTX 10 24 2018 Turing
mind-1-29 AMD EPYC 9554 2022 224 1133.4 L40S 10 48 2023 Ada Lovelace
CPU-Only Nodes
  • mind-0-15 / 0-16 / 0-17
    • CPU: AMD EPYC 7443
    • Cores: 48 physical / 96 logical
    • RAM: ~1 TB
    • GPU: None

Use cases: Preprocessing, statistical modeling, memory-intensive CPU workloads, neuroimaging pipelines.

GPU Architecture Summary
  • Blackwell (2025): RTX PRO 6000 (96 GB)
  • Ada Lovelace (2023): L40S (48 GB)
  • Ampere (2020–2021): RTX 3090, RTX A5000
  • Turing (2018): RTX 2080 Ti, TITAN RTX
  • Pascal (2017): TITAN Xp
Usage Guidance
  • CPU nodes: Preprocessing, statistical analysis, memory-heavy workloads.
  • RTX 2080 Ti / TITAN Xp: Legacy pipelines, imaging, lightweight GPU tasks.
  • RTX 3090 / A5000: General-purpose GPU computing and ML development.
  • TITAN RTX: Balanced GPU research workloads.
  • L40S: Large-scale deep learning training and inference.
  • Blackwell: Next-generation AI and high-memory model training.
Notes
  • Compute totals include compute nodes only.
  • Login, storage, and backup systems are not included.
  • All nodes are scheduled via SLURM.
  • All systems connected via 100 Gbps InfiniBand.
  • Storage systems are separate from compute infrastructure.
Updated on July 6, 2026
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