Complete Technical Guide: Flashing CMP 170HX & Unlocking 64 GB HBM2e on Ubuntu 22.04 LTS

# Complete Technical Guide: Flashing CMP 170HX & Unlocking 64 GB HBM2e on Ubuntu 22.04 LTS

This guide walks through the complete procedure to bypass factory OTP restrictions on the **NVIDIA CMP 170HX** (GA100 architecture, Device ID `10de:20c2` / `10de:20b0`) using **`CMPUnlocker`**. This restores disabled Streaming Multiprocessors (SMs) and unlocks the dormant HBM2e memory geometry (expanding 8 GB models up to 64 GB VRAM).

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## Technical Prerequisites & System Requirements

Before beginning, ensure your host server meets the following criteria:

* **OS:** Ubuntu 22.04 LTS or 24.04 LTS (x86_64).
* **Driver Target:** NVIDIA Open GPU Kernel Modules driver package (v580.x branch).
* **System Privileges:** Root / `sudo` access.
* **Hardware Cooling:** High-static-pressure forced airflow (4,000+ RPM fans in a 4U rackmount chassis) to prevent thermal shutdown on passive heatsinks.

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### Step 1: System Audit and Dependency Installation
First, confirm that your card is detected on the PCIe bus and install the Python 3 development environment and YAML parser required by the unlocker script.

```bash
# 1. Check for GA100 / CMP 170HX on the PCI bus
lspci -nn | grep -i nvidia
# Expected output should show Device ID 10de:20c2 or 10de:20b0

# 2. Update repository indices and install system dependencies
sudo apt update && sudo apt install -y \
  build-essential \
  python3 \
  python3-pip \
  python3-yaml \
  git \
  pciutils \
  wget

3. Verify PyYAML installation
python3 -c "import yaml; print(yaml.__version__)"

Step 2: Install NVIDIA Open-Source Kernel Drivers (Branch 580.x)

CMPUnlocker relies on specific register overrides within the NVIDIA GSP (GPU System Processor) firmware loaded by the nvidia-open 580 driver series.

# 1. Add the official Graphics Drivers PPA
sudo add-apt-repository ppa:graphics-drivers/ppa -y
sudo apt update

# 2. Install the open-kernel GPU driver and CUDA utils
sudo apt install -y nvidia-driver-580-open nvidia-utils-580

# 3. Prevent auto-updates from breaking the kernel modules
sudo apt-mark hold nvidia-driver-580-open

4. Verify GSP firmware presence
ls -la /lib/firmware/nvidia/580.*/gsp_tu10x.bin

Step 3: Backup Stock GSP Firmware

Always create a backup copy of the unmodified binary firmware file (gsp_tu10x.bin) before running the unlock patch.

# Locate your exact driver directory path
GSP_DIR=$(dirname$(ls /lib/firmware/nvidia/580.*/gsp_tu10x.bin | head -n1))

Create a persistent stock backup
sudo cp "${GSP_DIR}/gsp_tu10x.bin" "${GSP_DIR}/gsp_tu10x.bin.stock"
echo "Backup saved to ${GSP_DIR}/gsp_tu10x.bin.stock"

 

Step 4: Clone CMPUnlocker and Select VRAM Profile

Clone the source repository and set the default memory geometry target to unlocked_64gb for 8 GB physical variants.

# 1. Clone repository into local workspace
cd /opt
sudo git clone [https://github.com/amoghmunikote/cmpunlocker.git](https://github.com/amoghmunikote/cmpunlocker.git)
cd cmpunlocker

# 2. Inspect profile settings in constants configuration
# For 8 GB physical cards targeting 64 GB VRAM:
sudo ./install.sh --profile=8gb

# (Note: For rare 10 GB revision cards targeting 40 GB/80 GB, use --profile=10gb instead)

Step 5: Execute Cold Power Cycle

Unlike standard driver reloads, the initial WPR2 register unlock and SEC2 capacitor state clearing require a full cold boot. Warm soft-reboots will cause the unlock payload to fail on the first run.

# 1. Shut down the system completely
sudo poweroff

Operational Note: Once the server powers off, physically disconnect the AC power supply cables for 60 seconds to completely drain standby voltage from the motherboard and GPU board capacitors. Reconnect power and boot back into Ubuntu.

Step 6: Run Unlock Pipeline & Enable Systemd Daemon

Because register modifications do not survive deep power cycles natively, the CMPUnlocker background service monitors registers and automatically reapplies the patch on boot and driver reloads.

cd /opt/cmpunlocker

# 1. Run the unlock installer script with root privileges
sudo ./install.sh

# 2. Check the systemd service status
sudo systemctl status cmpunlocker.service

# 3. Stream daemon logs to confirm patch application
journalctl -u cmpunlocker -f -n 20

Step 7: Validate Unlocked Memory and Compute State

Query nvidia-smi and run a quick CUDA initialization script to confirm full compute throughput and VRAM recognition.

# 1. Verify SM clock speed limit removal and VRAM reporting
nvidia-smi --query-gpu=name,memory.total,clocks.max.sm --format=csv

# Expected Output:
# name, memory.total [MiB], clocks.max.sm [MHz]
# NVIDIA Graphics Device, 65536 MiB, 1410 MHz

# 2. Execute CUDA C-types test script in Python
python3 -c "
import ctypes
cuda = ctypes.CDLL('libcuda.so.1')
init_res = cuda.cuInit(0)
print(f'CUDA Init Status: {init_res} (0 = SUCCESS)')
"

Troubleshooting & Failure Modes

Issue / Symptom	Probable Cause	Corrective Action
nvidia-smi still reports 8 GB VRAM	GSP-RM register override or skipped cold reboot.	Perform a strict 60-second physical power drain. Ensure gsp_patch.py correctly updated sh_size during setup.
GPU drops off PCIe bus / Thermal throttling	Insufficient passive heatsink airflow.	Ensure high-CFM chassis fans pull air directly across the GPU fins. Passive desktop airflow is insufficient.
Kernel crash during heavy LLM load	Silicon defect on unlocked HBM2e stack.	Re-run ./install.sh --profile=40gb (or edit constants.yaml) to restrict VRAM allocation to a stable 32 GB/40 GB footprint.