CRNCH Rogues Gallery
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General Topics

  • What is the Rogues Gallery?
  • Getting Started with Rogues Gallery
  • Rogues Gallery Hardware
    • RG Virtual Machines
      • RG Virtual Machines
    • RG Physical Machines
      • Arm HPC
      • Near-Memory
      • Neuromorphic/AI
      • Reconfigurable and Novel Networking
      • Devboard Hosts
      • RISC-V
      • Simulation and Tutorial Machines
    • Techfee Systems
  • Rogues Gallery Filesystems
  • Mailing Lists and Requesting Help
  • Vendor Forums
  • Contributing to this Documentation

RG Workflows

  • Python Environments
  • Rogues Gallery Workflows
  • Using Scrontab with Slurm
  • Using Slurm with RG Systems
  • Using Slurm Examples
  • Open OnDemand
  • Using GUI Applications with VNC
  • GUI Applications with x2Go (Legacy)
  • Visual Studio Code
  • Jupyter Notebooks

Novel HPC

  • Instinct - AMD MI210
  • Quorra - NVIDIA Ampere GPUs
  • Octavius - A64FX Testbed

Lucata Pathfinder

  • Lucata Pathfinder Getting Started
  • Lucata Pathfinder FAQs

Novel Networking

  • Smart Networking - Getting Started
  • Bluefield-2 DPU

Reconfigurable Computing

  • Xilinx FPGAs - Getting Started
  • Xilinx Vivado Flow
  • PYNQ cluster
  • Xilinx Smart SSD
  • Vortex RISC-V GPGPU
  • Intel OneAPI for Reconfigurable Computing
  • FPGA Power Measurement

RISC-V

  • RISC-V Hardware
  • Vortex RISC-V GPGPU

Miscellaneous

  • Power Monitoring

Educational Resources

  • CRNCH Rogues Gallery Tutorials
  • Near-memory Resources
  • GraphBLAS Resources
  • Neuromorphic Computing Resources
  • Quantum Computing Resources
  • Related Testbed Resources
CRNCH Rogues Gallery
  • Docs »
  • Rogues Gallery Hardware
  • Edit on GitHub

Rogues Gallery Hardware¶

The Rogues Gallery testbed is composed of both “virtual” resources and “physical” servers and test platforms. The figure below shows the Rogues Gallery resources at a high level with suggested paths from development VMs to the actual hardware. Discussion of the filesystems you have access to can be found here.

For instance, if you’re able to test your compilation and do debugging on the rg-fpga-dev VMs, you can then use the same code on the physical “flubber” boxes to test your code with a PCI Express-based FPGA. We currently have three pairs of development VMs that map to physical hardware, as described more in the tables below.

Rogues Gallery Hardware

RG Virtual Machines¶

Note that VMs are meant as development resources since we may need to reboot physical hardware often to apply new drivers or reconfigure for specific experiments. These VMs have limited CPU cores and memory, but we can reconfigure them as needed or provide additional resources for long-running simulations. Local storage refers to space hosted within the VM for /localscratch. Except where noted, all machines are running RHEL8 or Ubuntu 20.04.

RG Virtual Machines¶

Resource CPU Memory (GB) Local Storage (GB) Software and Features
rg-emu-dev 4 core, E312xx 4 33 Emu simulator and tools
rg-fpga-dev<1-3> 4 core, E312xx 16 250 RHEL 8 VM for FPGA tools
rg-fpga-dev4 4 core, E312xx 16 250 Ubuntu 20.04 VM for FPGA tools
rg-neuro-dev 4 core, Broadwell 8 450 ROS, FPAA tools
rg-quantum-dev 4 core, Broadwell 8 130 XACC, Qiskit

RG Physical Machines¶

Arm HPC¶

Resource CPU Memory (GB) Network Cards Notes
octavius<1-16> A64FX 32 GB HBM2e EDR IB    

Near-Memory¶

The Pathfinder system consists of 4 chassis while the Emu Chick is a one chassis system. We recommend that you use the newer Pathfinder system for your work.

Resource Nodes Memory (GB) LCEs Network Notes
pathfinder (4 chassis) 32 2048 784 RapidIO 2.0, 10 GE  
karrawingi (Emu Chick, 1 chassis) 8 512 64 RapidIO, 1 GE karrawingi-login

Neuromorphic/AI¶

Resource CPU Memory (GB) Network Cards Notes
quorra1 2x AMD EPYC 7502 (Rome) 256 DDR4, 3200 MHz, 16 GB DIMMs Bluefield-2 NIC, 10 GE 4x A30  
quorra2 2x AMD EPYC 7502 (Rome) 256 DDR4, 3200 MHz, 16 GB DIMMs Bluefield-2 NIC, 10 GE 4x A30, 1x A100  
rg-fpaa-host Raspberry Pi Model 3B 2 GB     Hosts FPAA via USB UART connection
rudi1         Jetson Xavier NX Developer Kit

Reconfigurable and Novel Networking¶

Resource CPU Memory (GB) Network Cards Notes
flubber1 2x Intel E5-2630 256 DDR4, 2133 MHz, 32 GB DIMMs 10 GE 2x Alveo U50, Coral TPU NA
flubber2 2x Intel Gold 6226R 384 DDR4, 2666 MHz, 32 GB DIMMs 10 GE Arria 10 PAC, Bittware 520N NA
flubber3 2x Intel Gold 6226R 384 DDR4, 2666 MHz, 32 GB DIMMs 10 GE, EDR IB Stratix 10 PAC, Bittware 520MX, Bittware 385A-SoC NA
flubber4 2x AMD EPYC 7513 (Milan) 256 DDR4, 3200 MHz, 16 GB DIMMs NVIDIA ConnectX-6 NA NA
flubber5 2x AMD EPYC 7513 (Milan) 256 DDR4, 3200 MHz, 16 GB DIMMs NVIDIA ConnectX-6 Xilinx Alveo U280 NA
flubber6 2x AMD EPYC 7513 (Milan) 256 DDR4, 3200 MHz, 16 GB DIMMs NVIDIA ConnectX-6, Innova-2 Flex, Bluefield-1 NIC, Bluefield-2 NIC, Intel N6000 NA Smart Networking Node
flubber7 2x AMD EPYC 7513 (Milan) 256 DDR4, 3200 MHz, 16 GB DIMMs NVIDIA ConnectX-6, Innova-2 Flex, Bluefield-1 NIC, Bluefield-2 NIC, Intel N6000 NA Smart Networking Node
flubber8 2x Intel Gold 6338 512 DDR4, 3200 MHz, 32 GB DIMMs NVIDIA ConnectX-6 NA NA
flubber9 2x Intel Gold 6338 512 DDR4, 3200 MHz, 32 GB DIMMs NVIDIA ConnectX-6 NA NA
flubber10 2x Intel Gold 6338 512 DDR4, 3200 MHz, 32 GB DIMMs NVIDIA ConnectX-6 NA NA

Devboard Hosts¶

Resource CPU Memory (GB) Network Cards Notes
brainard2 i5-10210U 32 GB DDR4, 2666 MHz, 16 GB DIMMs 1 GE   Connection to RISC-V board and FPGA, Intel NUC10i5FNK

RISC-V¶

Resource CPU Memory (GB) Network Notes
johnny-rv5-1 4xU74 cores and 1xS7 core, 1.4 GHz 16 GB DDR4 1 GE SiFive Unmatched motherboard

Simulation and Tutorial Machines¶

Resource CPU Memory (GB) Network Notes
hawksbill / notebook 4x Intel E7-4820 1024 DDR3 1 GE Used for Jupyter notebooks

Techfee Systems¶

Resource CPU Memory (GB) Network Cards Notes
frozone<1-4> 2x Ice Lake 8352Y 256 DDR4, 3200GHz, 16 GB DIMMs Omni-Path 100 GB, 100HFA16LS 1.6TB P5800X SSD FY 2021 TechFee Acquisition
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