ParaTools Pro for E4S™- the Extreme-scale Scientific Software Stack – hardened for commercial clouds and supported by ParaTools, Inc. provides a platform for developing and deploying HPC and AI/ML applications. It features a performant remote desktop environment (based on VNC) on the login node and compute nodes interconnected by a low-latency, high bandwidth network adapter based on high-speed network interface cards such as AWS Elastic Fabric Adapter (EFA). ParaTools Pro for E4S™ features a suite of over 100 HPC tools built using the Spack package manager and the proprietary MVAPICH MPI tuned for commercial cloud platforms. It features ready to use HPC applications (such as OpenFOAM, LAMMPS, CP2K, Xyce, and Quantum Espresso) as well as AI/ML tools based on Python (such as NVIDIA NeMo™, TensorFlow, PyTorch, JAX, Horovod, Keras, OpenCV, SciKit Learn, and Pandas), supports Jupyter notebooks and the Codium IDE. New packages can be easily installed using Spack and pip and are accessible on the cluster compute and login nodes featuring NVIDIA GPUs. Job scheduling is supported using the Torque and SLURM batch schedulers. It may be used for developing the next generation of generative AI applications using a suite of Python tools and interfaces.

The Extreme-scale Scientific Software Stack (E4S) has built a unified computing environment for deployment of open-source projects. E4S was originally developed to provide a common software environment for the exascale leadership computing systems currently deployed at DOE National Laboratories across the US. ParaTools, Inc. is offering support for deploying and testing E4S products.

Support

Custom Cloud and Container Images

ParaTools, Inc. can create custom ParaTools Pro for E4S™ cloud images on AWS or other cloud providers. To discuss a custom quote for services including cloud or container development, please use the webform. 

Support for Adaptive Computing, Inc.’s ODDC 

ParaTools, Inc. supports Adaptive Computing, Inc.’s Adaptive.HPC/AI/ML-AS-A-SERVICE using ParaTools Pro for E4S™ on AWS using ODDC.