How to Use Servers for Collaborative Research
- How to Use Servers for Collaborative Research
This article details how to effectively utilize our servers for collaborative research projects within the wiki environment. It covers server access, data storage, computational resources, and best practices for maintaining a stable and productive research workflow. This guide is intended for researchers new to the server infrastructure. Please read this document thoroughly before initiating a large-scale project.
Server Access and Authentication
Access to our research servers is granted on a project-by-project basis. Requests should be submitted through the Project Access Request Form. Once approved, you will receive credentials consisting of a username and SSH key. Password authentication is **disabled** for security reasons. You will need an SSH Client to connect.
Here's a quick breakdown of the connection process:
| Step | Description |
|---|---|
| 1 | Obtain your username and SSH key from the system administrator. |
| 2 | Configure your SSH client to use the provided key. |
| 3 | Connect to the server using the hostname (provided with your credentials) and your username. Example: `ssh [email protected]` |
| 4 | You are now logged in and can begin working. Remember to review the Server Usage Policy. |
For more detailed instructions on setting up SSH keys, please refer to the SSH Key Management page. Any unauthorized access attempts will be logged and may result in account suspension. Always follow the Security Best Practices outlined on the wiki.
Data Storage and Management
Each research project is allocated a dedicated storage quota on the `/research` file system. This quota varies based on the project's needs, as determined during the access request process. It is crucial to manage your storage space efficiently. Avoid storing unnecessary files or duplicates. Regularly archive or delete old data following the Data Archiving Policy.
Here's a table outlining the available storage options and their recommended uses:
| Storage Type | Location | Recommended Use | Quota (Typical) |
|---|---|---|---|
| Project Directory | `/research/projectname` | Active research data, scripts, and temporary files. | 100 GB - 1 TB (variable) |
| Archive Directory | `/research/archive/projectname` | Long-term storage of completed datasets and results. | 500 GB - 5 TB (variable) |
| Shared Data Directory | `/research/shared` | Data accessible to multiple projects (use with caution and coordination). | 1 TB (shared) |
Backups are performed nightly. However, these backups are primarily for disaster recovery and should **not** be relied upon for routine data recovery. Researchers are responsible for maintaining their own backups of critical data. Consider utilizing rsync or other backup tools. Refer to the Backup Procedures document for details.
Computational Resources
Our servers offer a variety of computational resources, including access to high-performance computing (HPC) clusters. Access to the HPC cluster requires separate approval and training. Please see the HPC Access Guide.
Here's a summary of the server specifications:
| Server Type | CPU | Memory (RAM) | Storage | Operating System |
|---|---|---|---|---|
| Standard Research Server | Intel Xeon E5-2680 v4 (14 cores) | 64 GB | 1 TB SSD | CentOS 7 |
| HPC Node | Intel Xeon Gold 6248R (24 cores) | 128 GB | 2 TB NVMe SSD | CentOS 8 |
| Data Analysis Server | AMD EPYC 7763 (64 cores) | 256 GB | 4 TB HDD + 1 TB SSD | Ubuntu 20.04 |
Available software packages are managed through the Software Repository. If you require software not available in the repository, you can submit a request through the Software Installation Request Form. Be mindful of resource usage and avoid monopolizing server resources. Utilize job scheduling tools like Slurm when running computationally intensive tasks. See the Job Scheduling Guide for further information. Always monitor your processes using tools like `top` or `htop`.
Collaboration and Version Control
Effective collaboration is essential for successful research. We strongly recommend using Git for version control of your code and data. Our servers provide access to a GitLab instance for hosting your repositories. This allows for easy collaboration, code review, and tracking of changes.
Furthermore, utilize the wiki itself for documentation and knowledge sharing. Create dedicated pages for your project, outlining its goals, methodology, and results. Regularly update these pages to keep your collaborators informed. Consider using the Discussion Pages feature for asynchronous communication and brainstorming. Remember to cite all sources appropriately, following the Citation Guidelines.
Troubleshooting and Support
If you encounter any issues with the servers or software, please consult the FAQ. If you cannot find a solution, submit a support ticket through the Helpdesk. Please provide as much detail as possible, including error messages, steps to reproduce the issue, and your project name. The system administrators will respond to your ticket as quickly as possible. Please be patient, as response times may vary depending on the complexity of the issue. Always check the Server Status Page for known outages or maintenance schedules.
Main Page
Research Resources
Data Security
Server Usage Policy
Software Repository
Project Access Request Form
SSH Key Management
Security Best Practices
Data Archiving Policy
Backup Procedures
HPC Access Guide
Software Installation Request Form
Slurm
Job Scheduling Guide
GitLab
Discussion Pages
Citation Guidelines
FAQ
Helpdesk
Server Status Page
rsync
SSH Client
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️