FEP+
System Requirements
Supported Operating Systems
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.
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
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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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We support NVIDIA’s Multi-Instance GPU (MIG) feature. Please make sure that MIG-enabled GPUs are being used in conjunction with a queueing system which supports this feature, see How do I make use of Multi-instance GPUs (MIG).
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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.