System Requirements

 

  • Windows
  • Mac
  • Linux
  • GPGPU

Windows Supported Operating Systems

  • Windows 11

  • Windows 10

 

NOTES: 
We support English plus internationalized versions of the OS in Spanish, French, German, and Japanese.

All workflows that rely on Desmond are not supported on Windows or Mac platforms, they can only be run on Linux. This includes Molecular Dynamics, IFD-MD, FEP+, WaterMap, and a number of Materials Science workflows.

GPU machine learning applications such as Active Learning Glide and DeepAutoQSAR on GPU can only be run on Linux.

Timeline

We aim to provide support for new operating system versions 3 months after their public release.

Support cannot be provided once an OS platform version has reached "end of life" (EOL). Check with your platform provider for EOL information.

Upcoming Changes

In 2024-4 Schrödinger software uses Schrödinger License Manager by default. See Schrödinger License Manager Instructions. Existing FlexNet licensing can be used with the 2024-4 release by changing the settings. See FlexNet License Instructions.

 

To view a list of recent infrastructure changes that may require changes from your IT team click here.

Mac Supported Operating Systems

  • MacOS Sonoma (14)

  • MacOS Ventura (13)

  • MacOS Monterey (12)

 

NOTES:

We aim to support MacOS Sequoia (15)  in the 2025-1 release. The official MacOS 15 release date from Apple is too late in our release cycle to allow us to support it with the 2024-4 release.

Official support for the last MacOS 10x-based version ended with release 2023-1. Starting with release 2024-1, our software installer won't run on MacOS versions lower than MacOS11.

Once a Mac is upgraded to Big Sur or newer, versions of the Schrödinger suite prior to 2021-1 will not be able to be run.

All workflows that rely on Desmond are not supported on Windows or Mac platforms, they can only be run on Linux. This includes Molecular Dynamics, IFD-MD, FEP+, WaterMap, and a number of Materials Science workflows.

GPU machine learning applications such as Active Learning Glide and DeepAutoQSAR on GPU can only be run on Linux.

Timeline

We aim to provide support for new operating system versions 3 months after their public release.

Support cannot be provided once an OS platform version has reached "end of life" (EOL). Check with your platform provider for EOL information.

Upcoming Changes

In 2024-4 Schrödinger software uses Schrödinger License Manager by default. See Schrödinger License Manager Instructions. Existing FlexNet licensing can be used with the 2024-4 release by changing the settings. See FlexNet License Instructions.

 

To view a list of recent infrastructure changes that may require changes from your IT team click here.

Linux Supported Operating Systems

  • RedHat Enterprise Linux (RHEL) 8.8, 8.10, 9.2, 9.4

     

    Please make sure the listed packages are installed:

    Required packages 

sudo yum/dnf install <lib>

  • Rocky Linux 8.8, 8.10, 9.2, 9.4

     

    Please make sure the listed packages are installed:

    Required packages 

sudo yum/dnf install <lib>

  • Ubuntu 20.04 LTS, 22.04 LTS, and 24.04

     

    Please make sure the listed packages are installed:

    Required packages 

sudo apt-get install <lib>

 

NOTES:

All supported distributions have a glibc of 2.28 or greater.


If using NFS, file locking must be enabled.

Timeline

We aim to provide support for new operating system versions 6 months after their public release.

Support cannot be provided once an OS platform version has reached "end of life" (EOL). Check with your platform provider for EOL information.

Upcoming Changes

In 2024-4 Schrödinger software uses Schrödinger License Manager by default. See Schrödinger License Manager Instructions. Existing FlexNet licensing can be used with the 2024-4 release by changing the settings. See FlexNet License Instructions.

 

To view a list of recent infrastructure changes that may require changes from your IT team click here.

 

GPGPU

We support the following NVIDIA solutions:

Architecture Server / HPC Workstation
Pascal

Tesla P40

Tesla P100

 Quadro P5000
Volta

Tesla V100

 
Turing

Tesla T4

Quadro RTX 5000
Ampere

Tesla A100

RTX A4000

RTX A5000
Ada Lovelace

L4

 
Hopper

H100

 

 

How to configure queuing system license checking with Flexible GPU licensing

 

Deprecated

  • Support for the Tesla M40 and M60 cards is deprecated.

 

Notes

  • Standard support does not cover consumer-level GPU cards such as GeForce GTX cards.

  • In the 2024-2 release, the "Discounted Cores" of an L4 was decreased from 7424 to 5120. This adjustment was made to align with the L4's status as a preferred card due to its widespread availability on-premises and through cloud providers. Additionally, the L4's low power consumption, speed, and sufficient memory make it suitable for running the majority of workflows in a configuration with one GPU per node.

  • If you already have another NVIDIA GPGPU and would like to know if we have experience with it, please contact our support at help@schrodinger.com.

 

Hardware Requirements

  Required Strongly Recommended
Processor (CPU)

x86_64 compatible processor

(Apple silicon M-series processors are supported)

For large jobs, computing on a cluster with a queueing system is recommended, with the following hardware components:

  • A highly capable file server for the external network.

  • Shared storage for the intra-cluster network, to reduce traffic to and from the external network.

  • Fast processors, large memory, and high-quality motherboards and network interfaces, especially on the management nodes.

System memory (RAM)

4 GB memory per core

RAM is not related to the input file size, only the disk space is related.
Disk space 18 GB disk space for software installation; 400-500 GB if databases (PDB, BLAST, etc.) are also installed

60 GB minimum scratch disk space for running jobs

Faster local disk access is important for jobs that read a lot of data. For example, using SSD, a disk with a higher speed (e.g. 10000 rpm), or a disk array that uses multiple controllers and striping can be beneficial.

Local disks are preferred over networked disks for temporary storage (or for data that is used often) because networked disks are affected by network access, bandwidth, and network traffic.

 

 

 

Supported Queueing Systems

 

To run jobs on a remote host, a queueing system is required.

 

Supported Features

Queuing system License Checking Native GPU support version
PBS Pro

Yes

11.0
LSF

Yes

 9.1
Univa Grid Engine

Yes

8.1
Sun Grid Engine, Open Grid Scheduler

Yes

None
Torque

No

2.5.4
Slurm

Yes (Slurm version >= 18.08.2)

2.2

 

See Setting Up License Checking for Queueing Systems for more information on setting up license checking.

 

 

Extra considerations for visualization and interacting with Maestro

GPU

We recommend using a graphics card that supports hardware-accelerated OpenGL with at least 1GB onboard memory and an up-to-date vendor-supplied graphics driver.

Network file share

Using a networked file share mounted via CIFS (Samba) is not recommended, as Maestro projects use SQLite databases that have locking dependencies not typically available on them.

Mouse

We recommend using a 3-button mouse with a scroll wheel. Learn more about how to customize the actions performed by the mouse buttons and wheel in the Customize Mouse Actions Panel.

Requirements for working from home

Find best practices on how to work from home with the Schrödinger Suite.

3D stereo display

For a 3D stereo display, we recommend Looking Glass Monitors.

Remote display

A local installation of Maestro on your laptop or workstation will always run better than running it from a remote compute resource. If you need to run Maestro remotely, various protocols exist for virtual desktops with varying degrees of compatibility with OpenGL, Qt, and other graphics dependencies that Maestro has. Support for such protocols is outside of our control.

We strongly recommend against running Maestro via basic X11 forwarding, e.g., via “ssh -X workstation”, as the performance will be poor.

Coupling an up-to-date version VirtualGL (www.virtualgl.org) with a remote desktop protocol can make a remote session almost as responsive as a local environment. Once installed, you will launch Maestro as:

vglrun $SCHRODINGER/maestro

Typical “compute nodes” on HPC environments often do not have high quality graphics cards and are not optimal for running Maestro; their graphics hardware is often dedicated to GPU computing.

 

 

System requirements for individual products

 

Active Learning Glide

GPU Shape

QSite

 
 

DeepAutoQSAR

IFD-MD

WaterMap

 
 

Desmond

Jaguar

   
 

FEP+

Prime