INQUIRE Lab researchers use Devola, Surena, and Yorha for AI, sensing, simulation, and computing research. Docker-based access lets students run reproducible environments while the lab keeps the GPU pool shared, expandable, and useful for many projects.
Surena
Professional high-memory GPU node
Yorha
Six-GPU compute system
Devola
Mixed-GPU research workstation
Compute Systems
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Current model
Docker containers + shared GPU scheduling
Mixed-GPU research workstation
GPU profile
RTX 5090, RTX 3090, RTX 3080 Ti, and RTX 4080 SUPER class GPUs
Devola supports high-throughput experimentation across AI, sparse computing, simulation, and systems research. Its mixed GPU pool gives students practical access to several accelerator generations.
Professional high-memory GPU node
GPU profile
NVIDIA RTX PRO 6000 accelerators
Surena is built for researchers who need professional GPUs for large models, high-memory workflows, visualization, and data-intensive scientific computing.
Six-GPU compute system
GPU profile
Six installed GPUs, with additional expansion planned
Yorha gives the lab a dedicated six-GPU platform for parallel experiments, multi-user research jobs, and fast iteration on containerized workloads.
Multi-GPU systems support deep learning, neuromorphic computing, sensing, computer vision, and scientific simulation.
Students and researchers use isolated containers so dependencies stay reproducible while GPU resources remain shared.
The lab can assign compute environments by project, course, or researcher without requiring a dedicated workstation for each student.
The GPU pool is designed to grow as research demand increases while keeping the workflow stable for students.
The facility is designed for mentoring, coursework, research prototypes, and publishable experiments that need more GPU access than an ordinary workstation can provide.
Containerized environments for repeatable experiments
Shared GPUs for students, researchers, and project teams
Hardware available for AI, sensing, quantum-inspired, and systems workloads
Upcoming GPU expansion to increase lab-wide compute capacity
