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Computer Science Servers

Dahj, Soji

Supermicro server

  • ARM Neoverse N1 128-core processor
  • 1 TB of RAM
  • Linux operating system

The systems are remotely accessible as dahj.cs.purdue.edu and soji.cs.purdue.edu.


MC17

Dell PowerEdge R900 server

  • Four Intel Xeon E7450 2.40GHz 6-core processors
  • 24 GB of RAM
  • Linux operating system

The system is remotely accessible as mc17.cs.purdue.edu.

This server is scheduled to be retired in May 2025 (after the end of the semester)


MC18

Dell PowerEdge R420 server

  • Two Intel Xeon E5-2690 2.90GHz 8-core processors
  • 192 GB of RAM
  • Linux operating system

The system is remotely accessible as mc18.cs.purdue.edu.

This server was provided through a generous donation from the Intel Corporation.


MC19

Dell PowerEdge R815 server

  • Four AMD Opteron 6276 2.30GHz 8-core processors
  • 128 GB of RAM
  • Linux operating system

The system is remotely accessible as mc19.cs.purdue.edu.


MC20

Dell PowerEdge R520 server

  • Two Intel Xeon E5-2470 2.30GHz 8-core processors
  • 128 GB of RAM
  • Linux operating system

The system is remotely accessible as mc20.cs.purdue.edu.


MC21

Dell PowerEdge R520 server

  • Two Intel Xeon E5-2470 v2 2.40GHz 10-core processors
  • 96 GB of RAM
  • Linux operating system

The system is remotely accessible as mc21.cs.purdue.edu.


MCTESLA

Supermicro SuperServer 7046GT-TRF

  • Two Intel Xeon X5690 3.46GHz 6-core processors
  • 48 GB of RAM
  • Linux operating system
  • Four NVIDIA GeForce GTX 1060 GPU cards for CUDA/OpenCL programming

The system is not directly accessible to users. Compute (GPU) jobs can be submitted using Slurm from queue.cs.purdue.edu using queue mctesla-gpu. This is the same job submission system used on RCAC clusters (e.g. scholar.rcac.purdue.edu)


CUDA

Supermicro SuperServer 4028GR-TR

  • Two Intel Xeon E5-2667 3.20GHz 8-core processors
  • 128 GB of RAM
  • Linux operating system
  • Two EVGA GeForce GTX TITAN X GPU cards for CUDA/OpenCL programming
  • Four NVIDIA TITAN Xp GPU cards for CUDA/OpenCL programming

The system is not directly accessible to users. Compute (GPU) jobs can be submitted using Slurm from queue.cs.purdue.edu using queue cuda-gpu. This is the same job submission system used on RCAC clusters (e.g. scholar.rcac.purdue.edu)


GORMAN[12]

NVIDIA DGX-1

  • Two Intel Xeon E5-2698 v4 2.20GHz 20-core processors
  • 512 GB of RAM
  • Linux operating system
  • Eight NVIDIA Tesla V100 SXM2 32Gb GPU cards for CUDA/OpenCL programming

The systems are not directly accessible to users. Compute (GPU) jobs can be submitted using Slurm from queue.cs.purdue.edu using queue gorman-gpu. This is the same job submission system used on RCAC clusters (e.g. scholar.rcac.purdue.edu)


JACOBI[01-05,07-08]

Dell PowerEdge R820

  • Four Intel Xeon E5-4617 2.90Hz 6-core processors
  • 64 GB of RAM
  • Linux operating system

The systems are not directly accessible to users. Compute (CPU) jobs can be submitted using Slurm from queue.cs.purdue.edu using queue jacobi-all. This is the same job submission system used on RCAC clusters (e.g. scholar.rcac.purdue.edu)


Schedule

Last Updated: May 12, 2025 4:56 PM

Department of Computer Science, 305 N. University Street, West Lafayette, IN 47907

Purdue University Indianapolis, 723 W. Michigan St., Indianapolis, IN 46202

Phone: (765) 494-6010 • Fax: (765) 494-0739

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