Prerequisites and Support Matrix for MSA Search NIM#
Sequence Databases and Search Types#
The MSA Search NIM includes pre-indexed databases optimized for GPU Server operation:
Database Name |
Use Case |
Paired Search |
Template Search |
Source |
|---|---|---|---|---|
uniref30_2302 |
MSA and profile generation |
Yes |
Required |
|
colabfold_envdb_202108 |
MSA expansion |
No |
No |
|
pdb70_220313 |
Template search (70% cluster) |
No |
Yes |
|
pdb100_230517 |
Template search (100% cluster) |
No |
Yes |
|
pdb_20251028 |
mmCIF structure retrieval |
No |
Yes |
Total size: 1660 GB
Note
Paired MSA search requires databases with taxonomy information. Only uniref30_2302 supports paired search among the default databases.
Note
Template search requires uniref30_2302 for profile generation plus at least one template database (PDB70 or PDB100). The profile generated from Uniref30 is used to search the template databases for structural homologs.
Tip
To reduce storage requirements, you can use task-specific database profiles that load only the databases needed for your use case. Refer to Task-Specific Profiles and Custom Databases for details.
Supported Hardware#
Minimum System Hardware Requirements#
CPU Cores |
RAM (GB) |
NVMe SSD Storage (GB) |
GPU Count |
|---|---|---|---|
24 |
64 |
1660 |
One or more NVIDIA GPU from the Supported NVIDIA GPUs |
Supported NVIDIA GPUs#
The MSA Search NIM supports NVIDIA GPUs with at least 48 GB of GPU Memory. It has been tested on the following recommended configurations:
GPU |
GPU Memory (GB) |
GPU Count |
|---|---|---|
A100 |
80 |
1-8 |
H100 |
80 |
1-8 |
B200 |
180 |
1-8 |
L40S |
48 |
2-8 |
RTX 6000 Ada Generation |
48 |
2-4 |
Note
Starting with version 2.0.0, GPUs with 48GB memory (L40S, RTX 6000 Ada) require a minimum of 2 GPUs when using GPU Server (enabled by default). This is because GPU Server holds databases in memory for optimal performance.
Software Prerequisites#
Begin with Linux-based Docker-supported operating system
Install Docker - minimum version: 23.0.1
Install NVIDIA Drivers - minimum version: 580
Install the NVIDIA Container Toolkit - minimum version: 1.13.5
Verify your container runtime supports NVIDIA GPUs by running
docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi
Example output:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 580.82.07 Driver Version: 580.82.07 CUDA Version: 13.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA H100 ... On | 00000000:1B:00.0 Off | 0 |
| N/A 33C P0 75W / 700W | 1MiB / 81559MiB | 0% Default |
| | | Disabled |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Note
For more information on enumerating multi-GPU systems, see the NVIDIA Container Toolkit’s GPU Enumeration Docs
Supported CPU architectures: x86_64 / amd64.
NGC (NVIDIA GPU Cloud) Account#
To download and run the MSA Search NIM, you need an NGC account and API key:
Create an account on NGC if you don’t already have one
Generate an API Key - ensure that NGC Catalog is selected from the “Services Included” dropdown
Export the API key in your terminal:
export NGC_API_KEY=<your-api-key>
Log in to Docker with your NGC API key:
echo "$NGC_API_KEY" | docker login nvcr.io --username '$oauthtoken' --password-stdin
Note
Personal keys allow you to configure an expiration date, revoke, or delete the key using an action button, and rotate the key as needed. For more information about key types, refer to the NGC User Guide.