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Government Auction Update

Posted
By Usman Masood Ashraf
views 10 min read

Government Auction Update: Repurposing High-Performance Computing Gear for DevOps Environments

Introduction

When a Reddit user recently acquired 2,700 pounds of networking equipment from a government surplus auction, likely originating from Oak Ridge National Laboratory’s Appro Xtreme-X supercomputer “Beacon”, it sparked fascinating discussions about repurposing enterprise-grade hardware for modern DevOps environments. This incident highlights the growing trend of technologists acquiring decommissioned high-performance computing (HPC) equipment through government auctions - and the technical challenges that follow.

For DevOps engineers and system administrators, this scenario presents both opportunities and obstacles. Enterprise-grade hardware from research facilities often contains specialized components like Intel Xeon Phi coprocessors (specifically the Knights Corner architecture mentioned in the Reddit thread), InfiniBand networking gear, and custom blade server configurations. While these components were designed for scientific computing workloads, they can be repurposed for modern infrastructure-as-code environments, Kubernetes clusters, or continuous integration farms.

This comprehensive guide will explore:

  1. Technical identification of common HPC components found in government auctions
  2. Practical repurposing strategies for DevOps workflows
  3. Containerization approaches for specialized hardware
  4. Performance optimization considerations
  5. Security hardening of used enterprise gear

The supercomputing equipment being decommissioned today often contains components that are still relevant for modern containerized environments, particularly when dealing with parallel workloads or network-intensive applications. Understanding how to leverage these specialized components can give DevOps teams significant performance advantages while working with hardware that’s often available at auction prices.

Understanding HPC Hardware Repurposing

Historical Context of Government Surplus Hardware

Government research laboratories operate on upgrade cycles that typically span 3-5 years for their HPC systems. After this period, equipment is often sold through official surplus channels like GSA Auctions. The Oak Ridge Beacon system mentioned in the Reddit post was decommissioned in 2016 after serving since 2011, making its components prime candidates for such auctions.

Key Components and Their DevOps Applications

From the Reddit description, we can identify several key components and their potential modern applications:

  1. Intel Xeon Phi Coprocessors (Knights Corner):
    • Original purpose: Massively parallel processing for scientific workloads
    • Modern DevOps application: Machine learning training, video transcoding, cryptographic operations
    • Technical considerations: Requires specialized kernel support and modified container runtimes
  2. InfiniBand Networking:
    • Original purpose: High-throughput, low-latency inter-node communication
    • Modern DevOps application: Accelerated Kubernetes pod communication, distributed storage backends
    • Implementation example:
      1
2

      # Install InfiniBand drivers on Ubuntu
sudo apt-get install libibverbs-dev ibverbs-utils rdma-core
  3. Blade Server Chassis:
    • Original purpose: High-density computing in HPC clusters
    • Modern DevOps application: Hyperconverged infrastructure nodes, bare-metal Kubernetes clusters

Technical Challenges in Repurposing

The primary challenges when working with auction-acquired HPC gear include:

  1. Firmware Compatibility: Enterprise hardware often requires specific firmware versions that may no longer be available
  2. Power and Cooling Requirements: HPC components frequently have unusual power connectors and high thermal output
  3. Driver Support: Specialized accelerators may lack support in modern Linux kernels
  4. Proprietary Interfaces: Custom backplanes and interconnects may require undocumented protocols

Performance Considerations

When properly configured, repurposed HPC hardware can outperform modern consumer-grade equipment for specific workloads:

Workload TypeConsumer HardwareRepurposed HPC GearPerformance Delta
Parallel Batch Jobs1x baseline3-5x faster+300-500%
Network-IO Intensive1x baseline8-10x faster+700-1000%
Floating-Point Heavy1x baseline2-3x faster+100-200%

These performance characteristics make HPC gear particularly valuable for DevOps tasks like:

  • Distributed compilation farms
  • Large-scale container registry operations
  • Parallel testing environments
  • Machine learning pipeline execution

Prerequisites for HPC Hardware Implementation

Hardware Requirements

  1. Compatibility Verification:
    • Check CPU architecture compatibility (many HPC systems use Intel MIC or POWER architectures)
    • Verify RAM compatibility (FB-DIMM vs. standard DDR modules)
    • Confirm PCIe lane availability for accelerator cards
  2. Power Infrastructure:
    • 220V circuits for high-density racks
    • Redundant PSU support
    • Proper circuit balancing
  3. Cooling Solutions:
    • Minimum 25 CFM per U of rack space
    • Containment systems for hot aisle/cold aisle separation

Software Requirements

  1. Operating System:
    • RHEL/CentOS 7+ or Ubuntu 18.04+ (with HWE kernel)
    • Custom kernel builds may be required for specialized hardware
  2. Dependencies:
    1
2
3

    # Common dependencies for HPC hardware
sudo apt-get install build-essential dkms linux-headers-$(uname -r) \
  libnuma-dev libpciaccess-dev pciutils
  3. Specialized Drivers:
    • Intel Manycore Platform Software Stack (MPSS) for Xeon Phi
    • Mellanox OFED for InfiniBand

Security Considerations

  1. Firmware Validation:
    • Always verify firmware checksums against manufacturer archives
    • Consider air-gapped initial testing for sensitive environments
  2. Physical Security:
    • Implement chassis intrusion detection
    • Secure boot configurations
  3. Network Isolation:
    • Initial deployment on isolated VLANs
    • MAC address filtering for management interfaces

Installation and Configuration

Driver Installation for Xeon Phi Coprocessors

  1. Download the MPSS stack from Intel’s archived repository:
    1
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    wget https://registrationcenter-download.intel.com/akdlm/irc_nas/8364/mpss-3.8.6-linux.tar.bz2
tar -xjvf mpss-3.8.6-linux.tar.bz2
cd mpss-3.8.6
  2. Install dependencies and build:
    1
2

    sudo ./install.sh --default
sudo mpss-start
  3. Verify detection:
    1
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    micctrl --initdefaults
micinfo

InfiniBand Configuration

  1. Install OFED drivers:
    1
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    wget https://www.mellanox.com/downloads/ofed/MLNX_OFED-5.8-3.0.7.0/MLNX_OFED_LINUX-5.8-3.0.7.0-ubuntu20.04-x86_64.tgz
tar -xzvf MLNX_OFED_LINUX-5.8-3.0.7.0-ubuntu20.04-x86_64.tgz
cd MLNX_OFED_LINUX-5.8-3.0.7.0-ubuntu20.04-x86_64
sudo ./mlnxofedinstall
  2. Configure subnet manager:
    1

    sudo opensm -B /etc/opensm/opensm.conf
  3. Verify connectivity:
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    ibstat
iblinkinfo

Container Runtime Configuration

To leverage specialized hardware in containerized environments:

  1. Configure Docker to expose Xeon Phi devices:
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    # Create udev rule
echo 'SUBSYSTEM=="mic", MODE="0666"' | sudo tee /etc/udev/rules.d/99-mic.rules
sudo udevadm control --reload-rules

# Create Docker device mapping
sudo dockerd --device /dev/mic0 --device /dev/mic1
  2. Kubernetes device plugin setup: ```yaml

    xeon-phi-device-plugin.yaml

    apiVersion: v1 kind: Pod metadata: name: xeon-phi-device-plugin namespace: kube-system spec: containers:

    • name: phi-plugin image: intel/mic-plugin securityContext: privileged: true volumeMounts:
      • name: device-plugin mountPath: /var/lib/kubelet/device-plugins volumes:
    • name: device-plugin hostPath: path: /var/lib/kubelet/device-plugins ```

Performance Optimization

NUMA Alignment for HPC Hardware

Modern HPC systems rely heavily on NUMA architecture. Proper alignment is crucial:

1
2

# Launch Docker container with NUMA constraints
docker run -it --cpuset-cpus=0-7 --cpuset-mems=0 your-image

InfiniBand Tuning for Container Networks

  1. Configure RDMA networks in Docker:
    1

    docker network create --driver=rdma --subnet=192.168.100.0/24 rdma-net
  2. Kubernetes CNI configuration for RDMA:
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    {
  "name": "rdma-net",
  "type": "rdma",
  "ipam": {
    "type": "host-local",
    "subnet": "192.168.100.0/24"
  }
}

Power Management Settings

Disable power saving features for consistent performance:

1
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3
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for governor in /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
do
  echo performance | sudo tee $governor
done

Operational Considerations

Monitoring Specialized Hardware

  1. Custom Prometheus exporters for Xeon Phi:
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    from prometheus_client import start_http_server, Gauge
import subprocess

MIC_TEMP = Gauge('mic_temperature', 'Xeon Phi temperature')
MIC_UTIL = Gauge('mic_utilization', 'Compute core utilization')

def collect_mic_stats():
    output = subprocess.check_output(['micinfo'])
    # Parse micinfo output
    # Update metrics

if __name__ == '__main__':
    start_http_server(9100)
    while True:
        collect_mic_stats()
        time.sleep(15)
  2. InfiniBand network metrics:
    1
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    # Install performance counters
sudo apt-get install infiniband-diags perftest

# Query port counters
ibportstate -D 0 1

Maintenance Procedures

  1. Firmware update process:
    1
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    # Xeon Phi firmware update
micflash -Update -device all -image ./flash.bin
  2. Thermal management checks:
    1

    watch -n 5 'sensors | grep -E "(Package id|Core|MIC)"'

Troubleshooting Common Issues

Device Detection Failures

  1. Check kernel messages:
    1

    dmesg | grep -i mic
  2. Verify PCI enumeration:
    1

    lspci -nn | grep -i 'Intel Corporation.*Phi'

Performance Degradation

  1. NUMA misalignment symptoms:
    1

    numastat -m
  2. InfiniBand link issues:
    1

    ibcheckerrors

Security Considerations

  1. Isolate management interfaces:
    1
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    # Create separate network namespace
ip netns add mgmt
ip link set eno1 netns mgmt
  2. Firmware verification:
    1

    openssl dgst -sha256 ./firmware.bin | grep [known-good-hash]

Conclusion

Repurposing government auction HPC hardware presents unique opportunities for DevOps engineers to create high-performance environments at significantly reduced costs. The process requires careful hardware evaluation, specialized driver configuration, and custom container runtime setups, but the performance benefits for parallel workloads can be substantial.

Key takeaways from this guide:

  1. Specialized components like Xeon Phi coprocessors require modified container runtimes but can accelerate specific workloads dramatically
  2. InfiniBand networking remains highly relevant for modern distributed systems
  3. Proper NUMA alignment and power management are critical for consistent performance
  4. Comprehensive monitoring is essential when working with legacy enterprise gear

For further exploration of these concepts, consider these resources:

As research facilities continue to upgrade their supercomputing infrastructure, the availability of high-performance components through government auctions will likely increase. Developing expertise in integrating these specialized components into modern DevOps workflows creates opportunities for significant performance gains while maintaining budget efficiency.

Government Auction Update: Repurposing High-Performance Computing Gear for DevOps Environments

Introduction

When a Reddit user recently acquired 2,700 pounds of networking equipment from a government surplus auction, likely originating from Oak Ridge National Laboratory’s Appro Xtreme-X supercomputer “Beacon”, it sparked fascinating discussions about repurposing enterprise-grade hardware for modern DevOps environments. This incident highlights the growing trend of technologists acquiring decommissioned high-performance computing (HPC) equipment through government auctions - and the technical challenges that follow.

For DevOps engineers and system administrators, this scenario presents both opportunities and obstacles. Enterprise-grade hardware from research facilities often contains specialized components like Intel Xeon Phi coprocessors (specifically the Knights Corner architecture mentioned in the Reddit thread), InfiniBand networking gear, and custom blade server configurations. While these components were designed for scientific computing workloads, they can be repurposed for modern infrastructure-as-code environments, Kubernetes clusters, or continuous integration farms.

This comprehensive guide will explore:

  1. Technical identification of common HPC components found in government auctions
  2. Practical repurposing strategies for DevOps workflows
  3. Containerization approaches for specialized hardware
  4. Performance optimization considerations
  5. Security hardening of used enterprise gear

The supercomputing equipment being decommissioned today often contains components that are still relevant for modern containerized environments, particularly when dealing with parallel workloads or network-intensive applications. Understanding how to leverage these specialized components can give DevOps teams significant performance advantages while working with hardware that’s often available at auction prices.

Understanding HPC Hardware Repurposing

Historical Context of Government Surplus Hardware

Government research laboratories operate on upgrade cycles that typically span 3-5 years for their HPC systems. After this period, equipment is often sold through official surplus channels like GSA Auctions. The Oak Ridge Beacon system mentioned in the Reddit post was decommissioned in 2016 after serving since 2011, making its components prime candidates for such auctions.

Key Components and Their DevOps Applications

From the Reddit description, we can identify several key components and their potential modern applications:

  1. Intel Xeon Phi Coprocessors (Knights Corner):
    • Original purpose: Massively parallel processing for scientific workloads
    • Modern DevOps application: Machine learning training, video transcoding, cryptographic operations
    • Technical considerations: Requires specialized kernel support and modified container runtimes
  2. InfiniBand Networking:
    • Original purpose: High-throughput, low-latency inter-node communication
    • Modern DevOps application: Accelerated Kubernetes pod communication, distributed storage backends
    • Implementation example:
      1
2

      # Install InfiniBand drivers on Ubuntu
sudo apt-get install libibverbs-dev ibverbs-utils rdma-core
  3. Blade Server Chassis:
    • Original purpose: High-density computing in HPC clusters
    • Modern DevOps application: Hyperconverged infrastructure nodes, bare-metal Kubernetes clusters

Technical Challenges in Repurposing

The primary challenges when working with auction-acquired HPC gear include:

  1. Firmware Compatibility: Enterprise hardware often requires specific firmware versions that may no longer be available
  2. Power and Cooling Requirements: HPC components frequently have unusual power connectors and high thermal output
  3. Driver Support: Specialized accelerators may lack support in modern Linux kernels
  4. Proprietary Interfaces: Custom backplanes and interconnects may require undocumented protocols

Performance Considerations

When properly configured, repurposed HPC hardware can outperform modern consumer-grade equipment for specific workloads:

Workload TypeConsumer HardwareRepurposed HPC GearPerformance Delta
Parallel Batch Jobs1x baseline3-5x faster+300-500%
Network-IO Intensive1x baseline8-10x faster+700-1000%
Floating-Point Heavy1x baseline2-3x faster+100-200%

These performance characteristics make HPC gear particularly valuable for DevOps tasks like:

  • Distributed compilation farms
  • Large-scale container registry operations
  • Parallel testing environments
  • Machine learning pipeline execution

Prerequisites for HPC Hardware Implementation

Hardware Requirements

  1. Compatibility Verification:
    • Check CPU architecture compatibility (many HPC systems use Intel MIC or POWER architectures)
    • Verify RAM compatibility (FB-DIMM vs. standard DDR modules)
    • Confirm PCIe lane availability for accelerator cards
  2. Power Infrastructure:
    • 220V circuits for high-density racks
    • Redundant PSU support
    • Proper circuit balancing
  3. Cooling Solutions:
    • Minimum 25 CFM per U of rack space
    • Containment systems for hot aisle/cold aisle separation

Software Requirements

  1. Operating System:
    • RHEL/CentOS 7+ or Ubuntu 18.04+ (with HWE kernel)
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This post is licensed under CC BY 4.0 by the author.