DEV Community: CTCservers

Why Dedicated Servers Are Essential for AI and GPU-Accelerated Workloads

CTCservers — Thu, 02 Apr 2026 11:44:06 +0000

Artificial Intelligence and machine learning are revolutionizing the tech landscape, but building these models requires immense computational power. Tasks like natural language processing, complex image recognition, and predictive analytics involve processing massive datasets at lightning speed something standard CPUs often struggle to handle sequentially.

That is where GPU-accelerated workloads on dedicated servers come into play. By leveraging thousands of efficient cores for parallel processing, GPUs can speed up model training and deep learning algorithms far beyond traditional systems.

While shared cloud hosting might be fine for standard web applications, mission-critical AI projects require dedicated infrastructure. Here is why dedicated servers are the superior choice:

Unmatched Power & Speed: Raw processing horsepower equipped with fast SSD/NVMe storage guarantees ultra-low latency.

100% Exclusive Resources: No shared RAM, storage, or processing power. You get zero interference from other tenants.

Enhanced Security: Isolated, single-tenant environments keep your sensitive, proprietary data safe.

Long-Term Cost Predictability: Avoid the unpredictable overhead and skyrocketing pay-as-you-go fees of shared cloud networks during heavy workloads.

As your datasets grow, your infrastructure needs to scale seamlessly. Having exclusive computing environments means developers can stop worrying about performance bottlenecks and focus entirely on building better neural networks.

Securing SSH on Arch Linux: A Step-by-Step Guide

CTCservers — Thu, 26 Mar 2026 11:50:47 +0000

SSH is the industry standard for managing Linux servers remotely, but default configurations leave you vulnerable to automated brute-force attacks. Here is a high-level blueprint for locking down your Arch Linux server:

1. Update & Optimize: Keep your system patched and use Reflector to ensure you are pulling from the fastest, most up-to-date Arch mirrors.

2. Install OpenSSH: Install the package and enable the service to start on boot.

3. Create a Dedicated SSH Group: Restrict system access by creating a specific user group strictly for SSH logins.

4. Harden Configuration Settings: Use drop-in config files to change the default port, completely disable root login, lower authentication limits, and restrict access to your dedicated SSH group.

5. Set Up Key-Based Auth: Passwords can be brute-forced; cryptographic keys cannot. Generate a modern keypair (like Ed25519) locally and push it to your server.

6. Disable Password Authentication: Once your key login is tested and working, disable password logins entirely to neutralize credential attacks.

Defense in Depth:
For a truly robust setup, pair these SSH configurations with a strict firewall (like UFW) to limit port access, and Fail2Ban to automatically block malicious IPs.

Ready to implement this on your server?
If you want to see the code, configuration file snippets, and exact bash commands to execute this setup, visit the website!

Beating Gaming Latency: Why Bare Metal at the Edge is the Future

CTCservers — Thu, 19 Mar 2026 11:22:41 +0000

In the fast-paced world of competitive online gaming, milliseconds mean the difference between winning and losing. While traditional cloud computing has revolutionized many industries, it isn't always enough for real-time multiplayer gaming where lag is the ultimate enemy.

To deliver a near-zero lag experience, the secret lies in combining Edge Computing with Bare Metal Servers:

The Power of the Edge:
By deploying game servers in localized data centers just 20 to 50 miles away from players, we drastically reduce the physical distance data has to travel. This drops ping times to sub-20ms, ensuring on-screen actions register instantly.
Eliminating the "Noisy Neighbor":
Standard cloud servers use virtualization, meaning you share resources with others. Bare metal servers remove this middleman. The game engine gets 100% direct, unshared access to the server's CPU, RAM, and network cards, guaranteeing a flawless "tick-rate" and consistent performance.
Cost & Security Benefits:
Bare metal allows for highly predictable performance without the hidden bandwidth and API fees common in traditional cloud hosting, all while providing full OS-level control for robust anti-cheat systems.

Want to dive deeper into how dedicated hardware and edge networks are shaping the future of multiplayer infrastructure?

Quick Setup Guide: WireGuard on Ubuntu 22.04

CTCservers — Fri, 13 Mar 2026 08:57:52 +0000

WireGuard is a modern, incredibly fast, and lightweight VPN protocol. Unlike bulky traditional VPNs, it uses a streamlined "lock and key" system that is easy to set up and highly secure. Here is a high-level overview of how to build your own secure gateway.

Note: This is a conceptual overview. If you want to see the actual code, configuration files, and exact terminal commands, please visit the website linked at the bottom of this article.

The Setup Process

1. Install & Generate Keys: Install WireGuard on your Ubuntu 22.04 server and generate a secure public and private key pair.

2. Allocate IPs: Choose private IPv4 and/or IPv6 address ranges for your server and connected devices (peers).

3. Configure the Server: Create the main configuration file to securely store your server's private key, assign the IP addresses, and define the listening port.

4. Update Network & Firewall: Enable IP forwarding on the server and set up NAT/masquerading rules so client traffic properly routes out to the public internet.

5. Start the Service: Set WireGuard to run as a persistent background service so your VPN tunnel starts automatically on reboot.

6. Configure the Client (Peer): Install WireGuard on your client device, generate its own key pair, and set up a client config file that dictates what traffic gets routed through the VPN.

7. Connect & Verify: Authorize the connection by adding the client's public key to the server. Finally, start the tunnel on your client and verify your traffic is secure!

Take control of your network privacy today.

The Hidden Enemy in Competitive Gaming: Understanding Ping and Latency

CTCservers — Tue, 10 Mar 2026 11:16:43 +0000

If you have ever missed a crucial shot in a game because your screen froze for a split second, you know exactly how frustrating lag can be. In the fast-paced world of competitive online gaming, a split-second delay can be the difference between a glorious victory and a frustrating defeat.

While your skills and reflexes are essential, your internet connection plays a massive role behind the scenes. Let's dive into the technical side of why this happens and how ping and latency can make or break your matches.

What are Ping and Latency?

Though often used interchangeably, they mean slightly different things in the networking world:

Ping is the specific measurement (in milliseconds) of the time it takes for a small packet of digital information to travel from your PC to the multiplayer game server and back. Imagine throwing a tennis ball against a brick wall; the ping represents the exact speed at which that ball returns to your hand. The lower your ping, the closer to "instantaneous" your game feels.

Latency is a broader term describing the total, end-to-end delay. It encompasses the entire network journey plus hardware processing times. This includes your wireless controller sending the signal, your PC processing the command, the network ping, the server's time to register the action, and your monitor's refresh time.

When you play with high latency, you are essentially playing in the past. Your PC shows you where the enemy was a fraction of a second ago, rather than where they actually are.

Does Ping Affect FPS?

A common misconception in the gaming community is that high ping drops your Frames Per Second (FPS). The short answer is no. FPS is strictly about how smoothly your PC's graphics hardware is rendering the game, while ping is about your network speed.

However, bad ping can trick you. High ping causes "rubber-banding"—where your character forcefully snaps back to their server-recognized location and stutters that feel exactly like bad FPS, even if your rig is running the game flawlessly.

Common Causes of Connection Delays

What actually causes these frustrating spikes?

Distance to the Server: Physics matters. The farther away you live from the game server, the longer the data travel time.

Network Congestion: If your household is streaming 4K movies or downloading large files, your game packets have to wait in line.

Wi-Fi vs. Cable: Wi-Fi signals suffer from interference and packet loss. An Ethernet cable is a gamer's best friend.

Poor Server Quality: Sometimes, it’s not you it’s the server. Overloaded or cheap hardware on the host's end will cause lag for everyone connected.

How to Fix It?
Want to see the ideal ping ranges, actionable tips to instantly improve your connection, and learn why peer-to-peer hosting might be ruining your multiplayer survival worlds?

Supercharge Your Infrastructure: Getting Started with Intel® QuickAssist Technology (QAT)

CTCservers — Thu, 05 Mar 2026 12:02:08 +0000

As data sets scale exponentially and workloads in AI, analytics, and high-speed networking become more demanding, maximizing CPU efficiency is more critical than ever.

If your applications heavily rely on data compression/decompression or complex cryptographic ciphers, you might be burning through valuable CPU cycles. Enter Intel® QuickAssist Technology (Intel® QAT).

What Is Intel® QAT?

Intel® QAT is a built-in workload accelerator integrated directly into the silicon of modern Intel® Xeon® Scalable processors (including the 4th Gen, 5th Gen, and the new Intel® Xeon 6 with E-cores). Instead of relying on power-hungry external PCIe add-in cards, QAT offloads and processes massive cryptography and data compression tasks right at the chip level.

Why Developers & Infrastructure Engineers Should Care:
Frees Up Core CPU Cycles: By offloading compute-heavy encrypt/decrypt and compression tasks, your primary CPU cores remain fully dedicated to core application execution.

Massive Performance Leaps: Benchmarks show up to 9x to 137x faster hardware-accelerated compression in Red Hat Enterprise Linux compared to standard software-based compression.

Lower TCO & High Scalability: Handle more simultaneous encrypted client connections (like VPNs, load balancers, or CDNs) with a smaller overall data footprint and fewer cores.

Storage Acceleration: Speeds up heavy backup and archiving tasks for distributed storage systems, supporting advanced algorithms like Zstandard for significant throughput improvements.

Whether you are optimizing enterprise databases like Microsoft SQL Server, speeding up hyperconverged infrastructure (HCI), or securing network traffic, Intel® QAT is a game-changer for modern, data-heavy applications.

Want to see the full performance benchmarks, learn how to assess your system design, and find out how to configure the QAT drivers and libraries?

AMD Schola v2 Tutorial: Training AI Agents in UE5 (AMD & Nvidia Compatible)

CTCservers — Fri, 27 Feb 2026 12:04:14 +0000

Dive into the next generation of reinforcement learning in Unreal Engine 5! AMD Schola is a free, hardware-agnostic (yes, it works perfectly on Nvidia too!) plugin that bridges your 3D UE5 environments with powerful Python AI frameworks like Stable Baselines 3 and Ray RLlib.

What's New in Schola v2?

Modular Architecture: A "plug-and-play" system that completely decouples your AI's "brain" (decision-making) from its "body" (Unreal Actor).

Imitation Learning: Native Minari dataset support lets you train AI using recorded human gameplay.

Dynamic Agent Management: Spawn and despawn AI mid-episode—perfect for Battle Royales and procedurally generated worlds.

Blueprint Power: Full Blueprint support for setting up your AI's vision and actions without writing C++.

Modern RL Support: Seamless compatibility with the latest tools like Gymnasium (1.1+), Ray RLlib, and Stable-Baselines3.

Getting Started
To jump in, you will need Unreal Engine 5.5+ and Python 3.10+.

(Note: If you want to see the installation steps, CLI commands, and the code to get this running, please visit the website!)

Ready to train smarter NPCs and build dynamic procedural behaviors?

Stop Website Crashes: The Essentials of DDoS Protection

CTCservers — Fri, 27 Feb 2026 03:50:37 +0000

If you manage a web app, a business site, or a popular blog, sudden downtime is more than just an annoyance it can cost you users, revenue, and your hard-earned reputation. One of the biggest and most common threats causing this downtime today is a DDoS (Distributed Denial of Service) attack.

What Exactly is a DDoS Attack?

To understand how disruptive it can be, imagine your website is a popular retail store. Suddenly, thousands of decoy cars arrive just to block the road, fill the parking lot, and jam the entrance. Your actual, paying customers are trapped in the traffic and eventually give up.

In the digital world, attackers use a "botnet" (an invisible army of hijacked devices) to flood your server with a massive wave of fake data requests. Your server tries to process everything at once, its resources become completely exhausted, and your site crashes offline.

Key Steps to Protect Your Infrastructure

Defending your site requires a proactive approach. Here are the core strategies to keep your server secure and your site online:

Set Up Server Auto-Scaling: Automatically expand server resources to absorb the initial shock of a traffic spike.

Use a Content Delivery Network (CDN): Spread traffic across a global network of servers to prevent your main server from being overloaded.

Monitor Traffic 24/7: Catch the early warning signs of unnatural traffic patterns.

Implement Rate Limiting: Control how many requests a single IP address can make to stop bots in their tracks.

Deploy Bot Challenges: Use CAPTCHAs during sudden spikes to verify real humans and drop malicious bots.

Upgrade to DDoS-Protected Hosting: Rely on specialized servers with built-in hardware and software that filter out DDoS traffic before it ever hits your pages.

Want to dive deeper into these security steps, compare standard hosting versus protected hosting, and learn how to build an emergency plan?

How to Build Your Own Private AI: Deploying Phi-3 with Ollama and a WebUI on Ubuntu 24.04

CTCservers — Mon, 23 Feb 2026 12:05:18 +0000

Large Language Models (LLMs) have fundamentally changed how we interact with artificial intelligence, powering everything from advanced coding assistants to everyday conversational bots. However, relying on cloud-based giants like OpenAI or Google means sending your private data over the internet and paying for ongoing API costs.

The solution is running AI locally. Highly efficient models like Microsoft's Phi-3 are leading this revolution, proving that you no longer need massive data centers to achieve incredible results. Phi-3 delivers state-of-the-art reasoning and performance while being compact enough to run smoothly on your own private GPU server.

To harness the power of models like Phi-3 on an Ubuntu 24.04 GPU server, we will use Ollama. Ollama is a powerful, developer-friendly tool that completely simplifies the process of downloading, managing, and running open-source LLMs. Instead of wrestling with complex Python environments, complicated dependencies, and manual weights loading, Ollama acts as a streamlined local API server. It handles the heavy lifting of model inference in the background, automatically utilizing your server's GPU to ensure lightning-fast generation speeds.

Finally, an AI model isn't very accessible if you can only interact with it through a command-line terminal. That's where the WebUI comes in. In this tutorial, we will outline how to build a lightweight, Flask-based Web User Interface that connects directly to your local Ollama instance. This setup will give you a sleek, browser-based chat experience—just like ChatGPT—but hosted entirely on your own hardware. By the end of this guide, you will have a fully functional, highly performant AI ecosystem that offers complete control over your privacy, performance, and costs.

Note: This article provides a high-level overview of the architecture and steps. If you want to see the exact code, terminal commands, and scripts to build this, please visit the website linked at the bottom of this post!

Prerequisites

Before diving into the setup, ensure you have the following:

An Ubuntu 24.04 server with an NVIDIA GPU.
A non-root user or a user with sudo privileges.
NVIDIA drivers installed on your server.

1. Install Ollama

Ollama provides a streamlined, lightweight environment for running powerful large language models (such as Phi-3) entirely locally. It simplifies the AI lifecycle by automatically managing model downloads, caching, and API serving. Plus, setting it up on Ubuntu 24.04 is a remarkably quick and frictionless process.

Ollama offers an automated shell script that installs everything you need in just a few moments straight from your terminal. Once the installation script sets up the necessary user groups and background services, all you have to do is reload your environment. From there, you can enable the Ollama service to start on boot and verify it is actively running by pinging its local port.

2. Run a Phi-3 Model with Ollama

With the Ollama backend up and running, you can now load the Phi-3 model; a compact, high-speed AI model ideal for local deployments on GPU-powered servers.

You can initiate the Phi-3 model directly through Ollama's built-in run command. If Phi-3 isn’t already on your system, Ollama handles the heavy lifting by downloading the model locally and immediately launching an interactive terminal session. This allows you to type messages and watch Phi-3 respond in real-time. Once you are finished testing its reasoning capabilities, you can safely exit the session to return to your standard prompt.

3. Use Ollama Programmatically with cURL

Beyond the terminal, Ollama excels via its local REST API—which is perfect for:

Building custom tools.

Integrating AI into your existing apps.

Testing complex prompts programmatically.

You can interact with the Ollama backend by sending a prompt to the Phi-3 model via a standard HTTP POST request. By sending a JSON payload containing the model name and your prompt, you bypass the terminal entirely. Ollama will return a structured JSON response containing the AI's generated text, context metrics, and processing duration, making it incredibly easy to parse for automated workflows.

4. Create a Flask WebUI for Chat Interface

Make interacting with Phi-3 more intuitive by creating a simple Flask WebUI. This interface lets you send prompts to the model, view responses instantly, and experience Phi-3 like a local ChatGPT!

Prepare the Environment: First, set up and activate an isolated Python virtual environment to keep your system clean, then install Flask and the necessary request libraries.

Build the Backend: Create a Flask application script. This script will set up a local web server and define a route that takes user input from the web page and forwards it to Ollama's local API generation endpoint.

Design the Frontend: Create a template folder and add an HTML index file. This file will serve as your visual chat interface, featuring a text area for inputs, a send button, and a JavaScript function to asynchronously fetch and display the AI's response.

Launch the UI: Start the Flask application and open your server's IP address on the designated port in your web browser.

You can now type your prompts for example, "Give me 3 startup ideas related to climate change" click send, and watch Phi-3 generate answers instantly right in your WebUI!

Final Thoughts
Running Phi-3 locally on Ubuntu 24.04 with Ollama gives you:

Complete control over AI inference.
Zero API keys or rate limits.
Full privacy for your sensitive data. With just a conceptual understanding of these steps, you are well on your way to installing Ollama, launching Phi-3, and creating a custom Flask WebUI for real-time chat.

PCIe Gen-5 SSDs & Exabyte Scale: The Storage Revolution Hitting Dedicated Servers

CTCservers — Thu, 19 Feb 2026 12:02:33 +0000

In an era where data is the most valuable commodity, the ability to store and access it at scale is a competitive necessity. If you manage a business, run heavy applications, or handle massive amounts of data, you already know that speed is everything.

In the world of dedicated servers, the processor (CPU) gets a lot of the spotlight. But right now, the biggest revolution is happening in storage.

Welcome to the era of PCIe Gen-5 SSDs and Exabyte-Scale storage.

What is a PCIe Gen-5 SSD?

PCIe (Peripheral Component Interconnect Express) Gen-5 is the latest generational leap in motherboard interface standards, completely redefining how data moves inside a dedicated server.

Think of the PCIe interface as the highway connecting your server’s storage drive to its CPU and RAM. A PCIe Gen-5 SSD utilizes this new standard to essentially double the data transfer speed per lane compared to the previous Gen-4 standard.

To visualize the evolution of these interfaces:

Gen-3: A great two-lane road.
Gen-4: A four-lane highway.
Gen-5: A massive, high-speed, eight-lane expressway with no speed limit.

While highly capable Gen-4 SSDs topped out at impressive read/write speeds of around 7,000 to 8,000 MB/s, Gen-5 SSDs shatter that ceiling, pushing speeds up to a blistering 14,000 MB/s. To put that into perspective, you could transfer an entire 4K movie in less than one second.

Whether your server is executing millions of tiny, randomized read/write operations or moving massive backup files, this exponential jump in speed ensures that your storage hardware is never the bottleneck.

What is "Exabyte Scale" Storage?

While Gen-5 handles the speed, Exabyte Scale handles the size. To understand an Exabyte, let's look at how data sizes grow:

1,024 Gigabytes (GB) = 1 Terabyte (TB)
1,024 Terabytes (TB) = 1 Petabyte (PB)
1,024 Petabytes (PB) = 1 Exabyte (EB) (More than a billion gigabytes!)

Operating at "exabyte scale" relies on a sophisticated hardware and software architecture that allows dedicated servers and massive data centers to link thousands of ultra-fast drives together perfectly. This complex network creates a unified, massive pool of storage that doesn't crash, slow down, or bottleneck, even when highly demanding artificial intelligence applications access it at the exact same time.

What This Means for Dedicated Servers

How does this actually help high-demand environments? Provisioning a dedicated server equipped with a PCIe Gen-5 SSD provides an immense competitive advantage:

Enterprise Database Management: Databases (like MySQL, PostgreSQL, or MongoDB) are constantly reading and writing thousands of tiny pieces of data. Because Gen-5 SSDs have double the bandwidth, complex database queries happen almost instantly.

Hyperscale Workloads (AI & ML): Artificial Intelligence and Machine Learning algorithms need to "read" millions of files to learn and make decisions. A Gen-5 drive acts as the ultimate intake valve, allowing your server's CPU/GPU to ingest and process external data at lightning speeds.

Maximum Overall Server Speed: Even basic server tasks become incredibly fast—from instant boot times and zero-lag virtualization to processing massive backups in minutes instead of hours.

Want to see the full storage speed comparison chart and learn how PCIe Gen-5 stacks up against traditional SSDs in real-world scenarios (like E-commerce checkouts and 8K Video Streaming)?

🔗 Read More on the CTCservers Blog

Step-by-Step Guide to Setting Up a LAMP Web Server on Ubuntu/Debian

CTCservers — Wed, 18 Feb 2026 09:09:50 +0000

Whether you are hosting a dynamic WordPress blog, a custom PHP application, or simply learning the ropes of server management, the LAMP stack remains the gold standard for web hosting.

LAMP stands for Linux, Apache, MariaDB, and PHP—a powerful suite of open-source software that powers a significant portion of the internet.

By combining the stability of Debian or Ubuntu with the robustness of the Apache web server, the data management of MySQL/MariaDB, and the scripting power of PHP, you create a flexible and secure environment ready to handle everything from small personal projects to enterprise-level traffic.

In this guide, I outline the logic behind installing, configuring, and securing your own LAMP server to give you full control over your web presence.

Prerequisites

Before diving into the installation, you will need:

Operating System: A running instance of Debian or Ubuntu (Desktop or Server edition).

User Privileges: A user account with sudo (root) privileges.

Internet Access: To download packages from repositories.

1. Updating the System

To ensure the most stable foundation for your web server and applications, it is highly recommended to begin with a pristine environment. The first step in any server setup is ensuring your package lists and installed software are up to date.

2. Installing Apache

Apache is the web server component of the stack. It listens for web requests and serves your website's files to the visitor. Once installed, you can verify it is working by accessing your server's IP address in a browser, which should display the default Debian/Ubuntu landing page.

3. Installing the Database and PHP

Next, you need the backend components. You will need to install MariaDB (the database server) and PHP (the scripting language), along with several PHP extensions that allow PHP to communicate with the database and handle common tasks like image processing and XML parsing.

4. Configuring the Database Server

Security is paramount when handling databases. After installation, it is crucial to run the secure installation script provided by MariaDB. This process helps you:

Set up authentication (unix_socket is recommended).
Remove anonymous users.
Disallow root login remotely.
Remove test databases. Once secured, you will need to create a specific database and a dedicated user for your web application.

5. Configuring the Firewall

Enhancing your server’s security is best achieved by configuring a firewall. On Ubuntu/Debian, UFW (Uncomplicated Firewall) is the standard tool. You will need to specifically allow traffic on Port 80 (HTTP) and Port 443 (HTTPS), as well as ensure your SSH port remains open so you don't lock yourself out.

6. DNS and SSL (Optional)

To make your server accessible via a domain name rather than an IP address, you will need to configure your DNS zone records. Additionally, for modern web standards, securing your site with HTTPS is a must. You can achieve this using tools like Certbot to fetch free certificates from Let’s Encrypt.

Get the Code

This post covers the architecture and steps required for the setup. To get the exact terminal commands, configuration scripts, and copy-paste code snippets to execute this installation, please visit the full tutorial on my website.

Unlock Local AI: Running ROCm and Ollama on the AMD RX 6600 (Ubuntu Guide)

CTCservers — Wed, 18 Feb 2026 08:05:23 +0000

Running modern machine learning workloads on AMD consumer GPUs is no longer a fringe experiment. This guide explores how to set up AMD ROCm on Ubuntu 22.04 using an RX 6600, enabling you to run Large Language Models (LLMs) like Llama 3.1 locally without cloud fees.

The Shift to Local AI on AMD

For a long time, Nvidia’s CUDA has held the crown for machine learning. However, AMD’s ROCm (Radeon Open Compute) platform has matured significantly, offering an open-source ecosystem for high-performance computing.

While ROCm is officially optimized for high-end workstation cards, it is entirely possible—and highly effective—to run it on consumer-grade hardware like the Radeon RX 6600 or 6600 XT. This opens the door for developers and hobbyists to train models, run inference, and experiment with AI tools like Ollama directly on their own desktops.

The Challenge: "Official" Support

If you have tried installing ROCm on an RX 6600 before, you might have hit a wall. The RX 6600 (gfx1032) is not explicitly listed in ROCm’s supported device list, which usually targets the RX 6800/6900 series (gfx1030).

However, with the right environment overrides, we can force ROCm to treat the RX 6600 like its big brother, unlocking full hardware acceleration.

What the Full Guide Covers

I have written a comprehensive, copy-paste-ready tutorial on my website that walks you through the entire process. The guide covers:

System Preparation: Setting up Ubuntu 22.04 kernel headers and user permissions.

The Install: Using the correct repositories (Jammy vs. Focal) to avoid dependency hell.

The Critical Override: The specific environment variables needed to bridge the gap between the RX 6600 and ROCm.

Ollama Configuration: How to edit system services to ensure Ollama sees your dedicated GPU instead of your integrated graphics.

Verification: Monitoring power draw and clock speeds to ensure you are actually using the GPU and not burning up your CPU.

Why do this?

By combining ROCm with Ubuntu and tools like Ollama, you can deploy large language models and experiment with AI in a cost-effective way. It gives you privacy, control, and zero latency—perfect for private inference or learning how LLMs work under the hood.

Get the Code

To see the full step-by-step commands, configuration files, and the exact environment variables needed to get this running, please visit the full tutorial on my website.