Tribhuvan University Super Computing¶

Welcome to TU High-Performance Computing (HPC)¶

Tribhuvan University provides a High-Performance Computing (HPC) environment designed to support advanced research and computational workloads. Our HPC infrastructure enables researchers, faculty, and students to run large-scale simulations, machine learning models, and scientific computations efficiently.

TU HPC

What is HPC?¶

High-Performance Computing (HPC) refers to the use of parallel processing to run complex calculations at high speed. TU's HPC cluster consists of powerful computing nodes, GPUs, and optimized software stacks, allowing researchers to process vast amounts of data faster than traditional computing environments.

Key Features of TU HPC¶

Powerful Compute Nodes – Multi-core CPU and GPU-based high-performance servers.
Parallel Computing – Run large-scale simulations and computations efficiently.
Scalable Storage – Secure, high-speed data storage for research projects.
SLURM Job Scheduler – Efficient workload management with automated job queuing.
AI & Machine Learning Support – Optimized environment for AI/ML workloads.
Scientific Software Stack – Pre-installed software for research and engineering applications.
User Support & Documentation – Guides, tutorials, and hands-on workshops.

Why Use TU HPC?¶

TU HPC is available for faculty, students, and researchers engaged in computationally intensive projects. Our infrastructure supports research in:

Artificial Intelligence & Machine Learning
Computational Physics & Chemistry
Climate & Environmental Modeling
Genomics & Bioinformatics
Engineering Simulations
Big Data Analytics

News & Maintenance¶

Latest News¶

[March 2025] 4 nodes is down at the cluster.
[Feburary 2024] Upcoming HPC training workshop for researchers.
[January 2024] Performance upgrade and system optimization.

Maintenance Schedule¶

March 10, 2025: Scheduled downtime for security updates.
April 5, 2025: Hardware maintenance on storage servers.
May 15, 2025: Cluster-wide software upgrades.

For real-time updates, visit our Status Page.

Getting Started¶

Step 1: Request an HPC Account¶

Access to TU HPC is granted to eligible researchers and students. To request an account, follow the Access Guidelines.

Step 2: Connect to the HPC Cluster¶

After receiving your credentials, connect to the cluster via SSH:

ssh username@tu-ip-address

For detailed instructions, visit the Getting Started Guide.

Step 3: Submit Your First Job¶

Learn how to run jobs using SLURM and optimize computing resources. See SLURM Job Submission for more details.

Documentation Structure¶

Access & Accounts – How to get started with TU HPC.
Job Scheduling – Running and managing jobs with SLURM.
Software & Modules – Using available software and environments.
Data Management – Storing and managing data on HPC.
Parallel Computing – Leveraging parallel computing techniques.
Best Practices – Guidelines for efficient HPC usage.

Need Help?¶

If you have any questions or require assistance, contact our HPC Support Team at madhav [dot] ghimire@cdp [dot] tu [dot] edu [dot] np

Accelerate your research with TU HPC! 🚀