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AI in Diversity

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# AI in Diversity: Server Configuration

This article details the server configuration required to effectively run "AI in Diversity," a suite of artificial intelligence tools designed to analyze and promote diversity, equity, and inclusion (DEI) within organizational datasets. It's geared towards newcomers to our MediaWiki site and provides a technical overview of the necessary hardware and software. This configuration is optimized for performance, scalability, and security, and is currently deployed across our primary data centers.

Overview

The "AI in Diversity" project leverages several AI models, including Natural Language Processing (NLP) for text analysis, Computer Vision for image and video assessment, and Machine Learning (ML) for predictive analytics. These models demand significant computational resources. This document outlines the server specifications, software stack, and networking requirements to support this workload. We utilize a distributed architecture to handle the large datasets involved and ensure timely results. Familiarity with Server Administration and Linux System Administration is recommended for those deploying or maintaining these servers.

Hardware Specifications

The server infrastructure is divided into three tiers: Data Ingestion, Model Training, and Inference. Each tier utilizes distinct hardware configurations.

Data Ingestion Tier

This tier is responsible for receiving, validating, and pre-processing data from various sources.

Component Specification Quantity per Server
CPU Intel Xeon Gold 6338 (32 cores) 2
RAM 256 GB DDR4 ECC Registered -
Storage 4 x 8TB SAS 12Gbps 7.2K RPM HDD (RAID 10) -
Network Interface 10 Gbps Ethernet 2
Power Supply 1600W Redundant 2

Model Training Tier

This tier houses the powerful GPUs necessary for training the AI models.

Component Specification Quantity per Server
CPU AMD EPYC 7763 (64 cores) 2
RAM 512 GB DDR4 ECC Registered -
GPU NVIDIA A100 80GB PCIe 4.0 8
Storage 2 x 4TB NVMe PCIe Gen4 SSD (RAID 1) -
Network Interface 100 Gbps InfiniBand 2
Power Supply 2000W Redundant 2

Inference Tier

This tier is optimized for serving trained models and providing real-time predictions.

Component Specification Quantity per Server
CPU Intel Xeon Silver 4310 (12 cores) 2
RAM 128 GB DDR4 ECC Registered -
GPU NVIDIA T4 16GB PCIe 3.0 4
Storage 1 x 2TB NVMe PCIe Gen3 SSD -
Network Interface 25 Gbps Ethernet 2
Power Supply 1200W Redundant 2

Software Stack

The software stack is crucial for enabling the AI models and managing the infrastructure.

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

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