
local-llm
A comprehensive guide for building and configuring a high-end local machine to run state-of-the-art LLMs, with detailed hardware choices, BIOS tuning, and Docker-based model serving.
该驱动将核心解锁序列直接嵌入 BIOS 作为 DXE 驱动,使得解锁在操作系统重装、硬盘更换和冷启动后仍然保持,同时包含安全检查以避免启用有缺陷的核心。
Credit to https://github.com/rw-r-r-0644 for creating an implementation of this unlock, which I used as a reference when making this driver
This is so it can run extremely early in the boot process and add a minimal amount of time to the boot of BC250s that are already known to have good cores. By placing this driver in the bios, it prevents drive failures, updates, or OS reinstalls from breaking the cpu core unlock.
Like the other methods of core unlock, for some reason it causes the reported GPU clocks to be wrong. I have not noticed any negative impact on GPU performance however, so it appears to just be a visual/reporting issue?
It is a standalone EDK II DXE driver for the AMD BC-250 that mirrors the SMU core-unlock sequence from rw-r-r-0664, from this repo: https://github.com/rw-r-r-0644/bc250-core-unlock
This build script generates an .ffs driver for insertion into an AMI BIOS DXE firmware
volume with UEFITool.
The driver reads the core presence mask at SMN 0x0115A870 via PCI config space on 00:00.0.
0xFF: exit and boot normally.0x77: send SMU Queue 3 message 0x98, verify the mask becomes 0xFF,
then issue a warm reboot.This should prohibit it from unintentionally enabling defective cores on unexpected core masks.
Bc250CoreUnlockPkg/
Bc250CoreUnlockPkg.dec
Bc250CoreUnlockPkg.dsc
Bc250CoreUnlockDxe/
Bc250CoreUnlockDxe.inf
Bc250CoreUnlockDxe.c
scripts/
build_ffs.sh
podman installed locally (or docker if you set CONTAINER_ENGINE=docker)edk2By default, the build helper uses the Tianocore Fedora 41 development container:
ghcr.io/tianocore/containers/fedora-41-dev:latestIt maintains a reusable edk2 checkout under:
.cache/edk2
If you already have a working host-side EDK
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A comprehensive guide for building and configuring a high-end local machine to run state-of-the-art LLMs, with detailed hardware choices, BIOS tuning, and Docker-based model serving.
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