AI in the New Caledonian Rainforest

From Server rental store
Revision as of 10:17, 16 April 2025 by Admin (talk | contribs) (Automated server configuration article)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

AI in the New Caledonian Rainforest: Server Configuration

This article details the server configuration powering the “AI in the New Caledonian Rainforest” project, a research initiative utilizing artificial intelligence to monitor and analyze biodiversity in the New Caledonian rainforest. This guide is intended for newcomers to the MediaWiki platform and provides a detailed overview of the technical infrastructure. Understanding this setup is crucial for anyone contributing to the project's data processing or system maintenance. Please refer to the Main Page for project overview.

Project Overview

The project focuses on real-time analysis of audio and visual data collected from remote sensors deployed within the rainforest. This data is processed using machine learning models to identify species, track population movements, and detect potential threats to the ecosystem. The servers manage data ingestion, model training, and real-time inference. See Data Acquisition for details on sensor deployment.

Server Infrastructure

The infrastructure is comprised of three primary server roles: Data Ingestion, Processing & Model Training, and API & Visualization. These roles are distributed across a cluster of dedicated hardware. We leverage Linux as the operating system for all servers.

Data Ingestion Servers

These servers are responsible for receiving data streams from the rainforest sensors. They perform initial data validation and storage. Crucially, they handle data buffering to prevent loss during network interruptions. For details on networking see Network Topology.

Server Name Role CPU RAM Storage Network Interface
kali-ingest-01 Data Ingestion Intel Xeon Gold 6248R (24 cores) 128 GB DDR4 ECC 10 TB RAID 6 HDD 10 Gbps Ethernet
kali-ingest-02 Data Ingestion (Backup) Intel Xeon Gold 6248R (24 cores) 128 GB DDR4 ECC 10 TB RAID 6 HDD 10 Gbps Ethernet

These servers utilize rsync for data replication between themselves, providing redundancy. Data is initially stored in a raw format before being transferred to the processing servers. See Data Formats for further details.

Processing & Model Training Servers

These servers handle the computationally intensive tasks of data pre-processing, feature extraction, model training, and model evaluation. They are equipped with high-performance GPUs. We use Python and TensorFlow for model building.

Server Name Role CPU RAM GPU Storage Network Interface
kali-process-01 Processing & Training AMD EPYC 7763 (64 cores) 256 GB DDR4 ECC NVIDIA A100 (80GB) 20 TB RAID 0 NVMe SSD 40 Gbps InfiniBand
kali-process-02 Processing & Training AMD EPYC 7763 (64 cores) 256 GB DDR4 ECC NVIDIA A100 (80GB) 20 TB RAID 0 NVMe SSD 40 Gbps InfiniBand
kali-process-03 Processing & Training AMD EPYC 7763 (64 cores) 256 GB DDR4 ECC NVIDIA A100 (80GB) 20 TB RAID 0 NVMe SSD 40 Gbps InfiniBand

Distributed training is performed using Horovod. Model weights are stored in object storage.

API & Visualization Servers

These servers provide an API for accessing processed data and models, as well as a web-based visualization interface. They are responsible for serving predictions to end-users and displaying results. We use Flask as the web framework.

Server Name Role CPU RAM Storage Network Interface
kali-api-01 API & Visualization Intel Xeon Silver 4210 (10 cores) 64 GB DDR4 ECC 2 TB NVMe SSD 1 Gbps Ethernet
kali-api-02 API & Visualization (Backup) Intel Xeon Silver 4210 (10 cores) 64 GB DDR4 ECC 2 TB NVMe SSD 1 Gbps Ethernet

The API documentation is available at API Documentation. The visualization interface provides interactive maps and charts of species distribution. See Visualization Tools.

Software Stack

The following software components are crucial to the operation of the system:

Security Considerations

Security is paramount. All servers are protected by a firewall and regularly updated with security patches. Access to the servers is restricted using SSH key authentication. Data is encrypted both in transit and at rest. Regular security audits are performed. See Security Protocol for details.

Future Enhancements

Planned enhancements include:

  • Increased GPU capacity for faster model training.
  • Implementation of a more robust data pipeline.
  • Integration with additional sensor types.
  • Development of more sophisticated machine learning models. See Roadmap.



Data Acquisition Network Topology Data Formats Linux Python TensorFlow rsync Horovod object storage Flask API Documentation Visualization Tools Ubuntu Server PostgreSQL MinIO Prometheus Grafana SSH key authentication Security Protocol Roadmap Main Page


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

Order Your Dedicated Server

Configure and order your ideal server configuration

Need Assistance?

⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️

Retrieved from "https://serverrental.store/index.php?title=AI_in_the_New_Caledonian_Rainforest&oldid=2653"