Blog
If neither wired LAN nor Wi-Fi works with the combination of an MSI PRO Z790-A MAX WIFI motherboard and Windows 11 Pro, go to MSI's website and install the LAN drivers. https://jp.msi.com/Motherboard/PRO-Z790-A-MAX-WIFI/support#driver From the page above, select LAN Drivers, download the
DIY GPU Machines
Without further ado, let's run some Python code on the GPU. 4.3 Writing GPU-Accelerated PyTorch Code in Jupyter Notebook STEP 1: Open a terminal and create a directory for the PyTorch project Enter the following commands: mkdir pytorch_pj cd pytorch_pj STEP 2: Launch Jupyter Notebook
DIY GPU Machines
In this installment, we install CUDA and PyTorch. 4.2 Installing CUDA (+cuDNN) and PyTorch Together Installing PyTorch also pulls in CUDA and cuDNN for you, so let's take advantage of that. STEP 1: Generate the PyTorch installation command With all the groundwork finally in place, it'
DIY GPU Machines
In this installment, we install Anaconda. Python applications are generally run inside a virtual environment created for each application. Two tools are commonly used to build such virtual environments: Anaconda, or Python's built-in venv. This time, we will go with Anaconda. 4.1 Installing Anaconda (the Python environment)
DIY GPU Machines
Hello! In this installment, we install the NVIDIA display driver so that we can use the GPU on Ubuntu. 3.2 Installing the NVIDIA Display Driver We will install the display driver that supports the GPU we purchased, an NVIDIA RTX 3090 Ti 24GB. 3.2.1 Downloading the Driver
DIY GPU Machines
Hello! In this installment, we configure Ubuntu after the OS installation. 3.1 Configuring Ubuntu 3.1.1 Updates on first boot At this point the Ubuntu OS installation is complete. If any updates are shown, such as an Ubuntu OS update or a language pack update, run those first.
DIY GPU Machines
Hello! Let's install Ubuntu 22.04 on the GPU machine from the USB drive we created last time. 2.0 Connect the LAN cable Before installing, connect a LAN cable to the GPU machine so that it has internet access. 2.1 Boot from the USB drive Insert
DIY GPU Machines
Hello! Starting with this installment, we move on to the software side of turning our GPU machine into an AI machine. The goal is to get the GPU working under Ubuntu and, ultimately, to reach the point where we can run inference with an LLM. 1. Creating a Ubuntu Installation
DIY GPU Machines
We are now in the final stretch of the build. Let's keep going! 1. Connect the motherboard power cable The 24-pin ATX cable is the one with the largest bundle of wires. First, plug it into the connector labeled M/B on the power supply side. Next, plug
DIY GPU Machines
This time, we finally install the star of the show: the graphics card. 1. Remove the PCI Express slot covers The graphics card goes into the PCI Express Gen 5 x16 slot, so we remove the cover for that position. Also, this graphics card occupies 4 slots, so we remove
DIY GPU Machines
This time, we will mount the motherboard in the case and take care of the various cable connections. 1. Fit the standoff screws The case comes with what are called standoff screws (spacers). We will screw these into the case. The standoffs are there to hold the motherboard in place
DIY GPU Machines
In this installment, we set up the motherboard and its main components. 1. Unboxing the Motherboard The motherboard we purchased this time is the ASRock Z690 Steel Legend WiFi 6E/D5. Let's open it up right away. When you open the box, the cables and manuals are stored
DIY GPU Machines
Yesterday I went to Akihabara and bought a total of about 415,000 yen worth of parts for a GPU machine, so here is a report. GPU Machine Parts * Motherboard: ASRock Z690 Steel Legend approx. 40,000 yen * Memory: Crucial desktop DDR5 32GB x 2 = approx. 30,000 yen * CPU:
DIY GPU Machines
Today it's time to buy the power supply, SSD, and case. Jun here. Once I pick up the power supply, SSD, and case, I should have everything I need. Let me take another look at the note that was left for me. (6) SSD: 1 TB or larger.
DIY GPU Machines
This time, let's consider whether consumer GPUs can be used for serious AI computation, and how they differ from professional GPUs, with a few comparisons along the way. For an AI startup like ours (and not only startups), there are three scenarios in which we use GPUs. 1.
DIY GPU Machines
This time, we select a graphics board (GPU) suited to AI work. Before getting into the main story, let's sort out the difference between a graphics board and a GPU. A graphics board is a key piece of hardware that handles image processing and AI computation in a