Built on the Industry Standard HPC Toolchain

We don't just deploy the stack; we tune the kernel parameters, debug the fabric, and optimize the scheduler logic.

We specialize in the deployment, tuning, and automation of these core platforms.

Workload Orchestration

Intelligent Scheduling & Resource Management

The scheduler is the heartbeat of the cluster. We move beyond default configs to implement topology-aware scheduling that respects your specific hardware geometry.

  • Fairshare Algorithms: Priority weighting for multi-tenant equity
  • cgroup Containment: Preventing memory leaks from crashing nodes
  • Hybrid Policies: Seamless bursting to AWS/Azure when queues overflow
$ squeue --format="%.8i %.9P %.8j %.8u %.2t %.10M %.6D %R" --sort=P
JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)
6362287 interact bash lchen R 3:57:00 1 node001
5634342 gpu dock_sim jdlong R 9:27:29 1 node003
6372016 gpu sys/dash yangs2 R 1:55:23 1 node004
6371428 interact bash taylors3 R 2:03:56 1 node009
6366516 cpu neosim jsmith R 2:32:27 1 node006
6365952 condo_9 ENVI rcresto R 2:34:36 1 node001
6200232 condo_21 vasp_job rnichol PD 0:00 1 (Priority)
6371093 gpu jupyter yangs2 R 4:25:16 1 node004

Fabric & Interconnects

Low-Latency Network Design

A cluster is only as fast as its fabric. We diagnose and resolve the "invisible" network congestion that standard monitoring tools miss.

  • Subnet Management: OpenSM tuning and routing algorithms
  • Driver Optimization: Tuning OFED parameters for specific message sizes
  • Topology Design: Non-blocking Fat Tree and Dragonfly architectures
$ ibstat mlx5_2
CA 'mlx5_2'
CA type: MT4123
Number of ports: 1
Firmware version: 20.35.1012
Hardware version: 0
Node GUID: 0xb83fd203004bc9d6
System image GUID: 0xb83fd203004bc9d6
Port 1:
State: Active
Physical state: LinkUp
Rate: 200
Base lid: 211
LMC: 0
SM lid: 1
Capability mask: 0xa651e848
Port GUID: 0xb83fd203004bc9d6
Link layer: InfiniBand

High Performance Storage

Parallel Filesystems & Data Lifecycle

Storage I/O is the most common bottleneck in modern HPC. We architect for massive throughput, ensuring your GPUs are never left starving for data.

  • Kernel Bypass: Direct NVMe access for microsecond latency
  • Tiering Automation: Policy-based movement from Flash to S3 Object Store
  • Metadata Tuning: optimizing for millions of small files (bio/genomics)
$ weka status
WekaIO v4.2.18.34 (CLI build 4.2.18.34)

cluster: apex-weka1
status: OK (205 backend containers UP, 512 drives UP)
protection: 16+2 (Fully protected)
hot spare: 1 failure domains (89.39 TiB)
drive storage: 5.50 PiB total, 1.63 PiB unprovisioned
cloud: connected
license: OK, valid thru 2027-06-01T12:08:04Z

io status: STARTED 631 days ago (1300 io-nodes UP, 5400 Buckets UP)
link layer: Infiniband + Ethernet
clients: 499 connected, 7 disconnected
reads: 11.94 GiB/s (33324 IO/s)
writes: 1.59 GiB/s (374422 IO/s)
operations: 654401 ops/s
alerts: 2 active alerts, use `weka alerts` to list them

Reproducible Science

Secure Container Runtimes

Dependency hell is the enemy of productivity. We implement Apptainer (formerly Singularity) to allow researchers to bring their own environments—running PyTorch, TensorFlow, or custom pipelines at near-native speed without compromising host security.

  • GPU Integration: Seamless pass-through for NVIDIA CUDA libraries
  • Bind Mounts: Auto-mapping high-performance storage (WEKA) into containers
  • SIF Build Pipelines: Automating container builds from GitHub Actions
$ apptainer exec --nv --bind /weka/data:/data \
./pytorch_latest.sif \
python3 /data/train_model.py --epochs 50

INFO: Underlay of /etc/localtime identified
INFO: NVIDIA Card detected: H100 (UUID: GPU-4b...)
TensorFlow: 2.14.0 | CUDA: 12.2 | Device: GPU:0
Training started...
Epoch 1/50: [==============================] - 4s 2ms/step

Immutable Infrastructure

Automated Config Management

A cluster that depends on manual tweaks is a ticking time bomb. We treat your OS (Rocky/RHEL) as code. Using Ansible, we ensure that every node, from the login servers to the compute nodes, is identical, version-controlled, and instantly reproducible.

  • Drift Detection: Automatically reverting manual changes to ensure stability
  • Rolling Updates: Patching the OS without draining the entire cluster
  • Security Hardening: Enforcing SELinux policies automatically
$ ansible-playbook site.yml -e "target=compute"

PLAY [Compute Nodes] ******************************************

TASK [kernel : Apply low-latency tuning profile] **************
changed: [node001]
changed: [node002]
changed: [node003]
changed: [node004]

TASK [security : Enforce SELinux Enforcing Mode] **************
ok: [node001]
ok: [node002]
ok: [node003]
ok: [node004]

PLAY RECAP ****************************************************
node001 : ok=14 changed=1 unreachable=0 failed=0
node002 : ok=14 changed=1 unreachable=0 failed=0
node003 : ok=14 changed=1 unreachable=0 failed=0
node004 : ok=14 changed=1 unreachable=0 failed=0
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