System Requirements
Supported Operating Systems
- Windows
- Mac
- Linux
Windows 11
Windows 10
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
Beginning in 2024-3, the Schrödinger software release will use Schrödinger License Manager by default. See Schrödinger License Manager Instructions.
Existing FlexNet licensing can be used with the 2024-3 release by changing the settings. See FlexNet License Instructions for 2024-3.
To view a list of recent infrastructure changes that may require changes from your IT team click here.
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MacOS Sonoma (14)
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MacOS Ventura (13)
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MacOS Monterey (12)
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
Beginning in 2024-3, the Schrödinger software release will use Schrödinger License Manager by default. See Schrödinger License Manager Instructions.
Existing FlexNet licensing can be used with the 2024-3 release by changing the settings. See FlexNet License Instructions for 2024-3.
To view a list of recent infrastructure changes that may require changes from your IT team click here.
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RedHat Enterprise Linux (RHEL) 8.8, 9.2
Please make sure the listed packages are installed:
sudo yum/dnf install <lib>
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Rocky Linux 8.8, 9.2
Please make sure the listed packages are installed:
sudo yum/dnf install <lib>
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Ubuntu 20.04 LTS and 22.04 LTS
Please make sure the listed packages are installed:
sudo apt-get install <lib>
Timeline
We aim to provide support for new operating system versions
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
Beginning in 2024-3, the Schrödinger software release will use Schrödinger License Manager by default. See Schrödinger License Manager Instructions.
Existing FlexNet licensing can be used with the 2024-3 release by changing the settings. See FlexNet License Instructions for 2024-3.
To view a list of recent infrastructure changes that may require changes from your IT team click here.
Hardware Requirements
Required |
|
|
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:
|
System memory (RAM) |
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RAM is not related to the input file size, only the disk space is related. |
Disk space |
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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. The following queueing systems are supported:
- PBS Pro
- Grid Engine, including SGE, Open Grid Scheduler, and Univa GE, minimum version 6.2
- LSF, minimum version 7.0.2
- Slurm, minimum version 2.1 (minimum version 18.08.2 for remote license checking, see Configuring Remote License Checking)
- Torque
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 |
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.
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.
GPGPU Requirements
(General-purpose computing on graphics processing units)
Listed here are the GPU computing requirements for Desmond, Deep AutoQSAR, FEP+, GPU Shape, and WaterMap.
Requirements for Jaguar, Active Learning and other products can be found on their individual pages below.
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 |
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Hopper |
H100 |
|
Deprecated
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Support for the Tesla M40 and M60 cards is deprecated.
Notes
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We support only the NVIDIA 'recommended / certified / production branch' Linux drivers for these cards with minimum CUDA version 12.0.
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For information on pre-configured Schrödinger compatible GPU boxes see MD Compatible Systems and FEP+ Compatible Systems.
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Standard support does not cover consumer-level GPU cards such as GeForce GTX cards.
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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.
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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.
System requirements for individual products
Active Learning Glide |
GPU Shape |
QSite |
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DeepAutoQSAR |
IFD-MD |
WaterMap |
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Desmond |
Jaguar |
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FEP+ |
Prime |