Sold by: ParaTools Inc.
Deployed on AWS
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This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Ubuntu, using AWS Parallel Computing Service (AWS PCS), with over 100 HPC and AI/ML tools, a remote desktop environment (Amazon DCV), and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, TensorFlow, and vLLM tuned for AWS Parallel Computing Service, with a complete HPC software stack including numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), performance evaluation tools (HPCToolkit, TAU), HPC applications (GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce).
Overview
ParaTools Pro for E4S™ - the Extreme-scale Scientific Software Stack, E4S™ hardened for commercial clouds and supported by ParaTools, Inc., provides a platform for developing and deploying HPC and AI/ML applications. It features an Amazon DCV remote desktop environment on the login node, with compute nodes interconnected by a low-latency, high-bandwidth network adapter based on AWS Elastic Fabric Adapter (EFA). ParaTools Pro for E4S™ features a suite of over 100 HPC tools built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for EFA utilizing SLURM for job management. It features ready-to-use HPC applications (GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Weather Research and Forecasting Model-WRF, Xyce) as well as AI/ML tools based on Python (Hugging Face Transformers, JAX, Keras, matplotlib, NVIDIA BioNeMo, NVIDIA NeMo™, OpenCV, PyTorch, TensorFlow, vLLM, with JupyterLab and Jupyter Notebook) and the VSCodium IDE. New packages can be easily installed using Spack and pip and are accessible on the cluster compute and login nodes. It may be used for developing the next generation of generative AI applications using a suite of Python tools and interfaces.
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 being deployed at DOE National Laboratories across the U.S. Support for ParaTools Pro for E4S™ is available through ParaTools, Inc. This product has additional charges associated with it for optional product support and updates.
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR), under SBIR Award Number DE-SC0022502 ("E4S: Extreme-Scale Scientific Software Stack for Commercial Clouds").
Note: This product contains repackaged and tuned open source software (e.g., E4S™, Spack and AI/ML tools like NVIDIA NeMo™, BioNeMo, PyTorch, JAX, vLLM, Keras, Hugging Face Transformers etc.) which is configured and linked against a proprietary MVAPICH-Plus 4 MPI implementation specifically developed and tuned for EFA.
The full list of E4S applications installed via Spack is as follows:
- adios
- adios2
- alquimia
- aml
- amrex
- arborx
- argobots
- ascent
- axom
- boost
- butterflypack
- cabana
- caliper
- chai
- chapel
- charliecloud
- conduit
- cp2k
- cusz
- darshan-runtime
- darshan-util
- datatransferkit
- dyninst
- e4s-alc
- e4s-cl
- exaworks
- faodel
- flit
- flux-core
- fpm
- gasnet
- ginkgo
- globalarrays
- gmp
- gotcha
- gptune
- gromacs
- h5bench
- hdf5
- hdf5-vol-async
- hdf5-vol-cache
- hdf5-vol-log
- heffte
- hpctoolkit
- hpx
- hypre
- kokkos
- kokkos-kernels
- laghos
- lammps
- lbann
- legion
- libcatalyst
- libceed
- libnrm
- libpressio
- libquo
- libunwind
- loki
- magma
- mercury
- metall
- mfem
- mgard
- mpark-variant
- mpifileutils
- nccmp
- nco
- nek5000
- nekbone
- netcdf-fortran
- netlib-scalapack
- nrm
- omega-h
- openfoam
- openmpi
- openpmd-api
- papi
- papyrus
- parallel-netcdf
- parsec
- pdt
- petsc
- phist
- plasma
- plumed
- precice
- pruners-ninja
- pumi
- py-cinemasci
- py-h5py
- py-jupyterhub
- py-libensemble
- py-petsc4py
- qthreads
- quantum-espresso
- raja
- rempi
- scr
- slate
- slepc
- stc
- strumpack
- sundials
- superlu
- superlu-dist
- swig
- sz
- sz3
- tasmanian
- tau
- trilinos
- turbine
- umap
- umpire
- upcxx
- veloc
- vtk-m
- wannier90
- warpx
- wps
- wrf
- xyce
- zfp
Highlights
- ParaTools Pro for E4S™ and Machine Learning stacks, including NVIDIA NeMo™ and BioNeMo, built and optimized for AWS EFA and AWS Parallel Computing Service (PCS)
- A proprietary MVAPICH-Plus 4 MPI implementation that offers lower latency and higher throughput than default OpenMPI implementations for pre-installed applications and user installed applications
- HPC software environment managed using the Spack package manager
Details
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Delivery method
Delivery option
64-bit (Arm) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 31 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
c6gn.16xlarge Recommended | $0.99 |
x8g.12xlarge | $0.99 |
r7gd.4xlarge | $0.99 |
hpc7g.16xlarge | $0.99 |
m6g.8xlarge | $0.99 |
is4gen.xlarge | $0.99 |
m7gd.12xlarge | $0.99 |
m6g.large | $0.99 |
m6gd.xlarge | $0.99 |
r8g.metal-48xl | $0.99 |
Dimensions summary
You pay by the hour based on the ARM64 (Graviton) EC2 instance type you run this software on with AWS Parallel Computing Service. Each dimension maps to a single instance type, so there are no tiers or plans to choose between. Pricing scales with the size and family of instance you select. Smaller instances (like t4g.nano or c6g.medium) carry lower hourly rates, while larger and metal instances (like x8g.48xlarge or r8g.metal-48xl) carry higher rates. You pick the instances that fit your HPC or AI/ML workload and pay only for the hours used.
Top-of-mind questions for buyers
Each hourly unit maps to one running ARM64 (Graviton) EC2 instance of the type you select. The rate covers the ParaTools Pro for E4S software running on that instance. AWS charges the underlying EC2 compute, storage, and networking separately. You pay for both together on the same AWS bill.
The software rate meters running instance-hours. Instances you stop or terminate stop accruing the hourly software charge. Because this runs with AWS Parallel Computing Service, compute nodes can scale up and down for jobs, so you pay only for the hours instances actually run. AWS storage fees may still apply to stopped instances.
Each instance type bills independently at its own hourly rate. If your cluster mixes a head node and several compute nodes of different types, each running instance accrues its matching hourly charge. Your total is the sum of all running instances' hours across the types you use.
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Any additional refund enquiries can be sent to support@paratools.com and will be considered individually on a case by case basis.
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Delivery details
64-bit (Arm) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
- AWS PCS: 1.4.0
- E4S release: 26.06
- Inter-node communication: EFA or Ethernet (EFA recommended for best MPI performance)
- Default MPI: MVAPICH4-Plus 4.1
- OS: Ubuntu 24.04
- DCV: 2025.0 (r20103) for remote desktop access
Critical (security): this version removes the GNU inetutils telnet server, remediating CVE-2026-32746 (telnetd LINEMODE SLC out-of-bounds write; pre-auth unauthenticated root RCE on port 23). No telnet or inetutils-telnetd package is present and nothing listens on port 23.
IMPORTANT:
- The MVAPICH4-Plus MPI shipped with this image supports both EFA and standard Ethernet for inter-node communication, but EFA is strongly recommended for best MPI performance. To get a list of instance types that are EFA compatible you can use the AWS CLI:
aws ec2 describe-instance-types --filters Name=network-info.efa-supported,Values=true \
--query InstanceTypes[*].[InstanceType] \
--output text | sort
- NVIDIA NeMo, NVIDIA BioNeMo and the AI/ML frameworks are installed into the system Python environment at /opt/python and are importable without activating a separate virtual environment.
Updates in this version:
- AWS PCS upgraded from 1.3.2 to 1.4.0
- E4S upgraded from 25.11 to 26.06
- Security: removed the inetutils telnet server (CVE-2026-32746)
- Refreshed E4S stack (ADIOS2 2.12.1, GROMACS 2026.1, HPCToolkit 2026.0.1, Kokkos 5.1.1, LAMMPS 20250722.3, OpenMPI 5.0.10, PETSc 3.25.1, Quantum ESPRESSO 7.5, SLATE 2025.05.28, SuperLU-dist 9.2.1, Trilinos 16.2.0)
- Refreshed ML tool stack (Hugging Face Transformers 5.6.0, JAX 0.10.1, Keras 3.14.1, NVIDIA BioNeMo, NVIDIA NeMo, PyTorch 2.11.0, SGLang 0.5.12, TensorFlow 2.21.0, vLLM 0.21.0)
- Docker 29.6.0; Podman 4.9.3; Singularity-CE 4.4.2; NVIDIA Container Toolkit 1.19.1
- Ollama 0.30.11; Julia 1.12.6; Go 1.26.4
ParaTools Pro for E4S (TM) provides a turn-key cloud HPC solution with the E4S Software stack and machine learning tools and SDKs installed and optimized to run on AWS. The key software features and versions installed are:
- Ubuntu 24.04, arm64
- Amazon DCV 2025.0 remote desktop
- VSCodium IDE 1.121.03429
- E4S 26.06 CPU and CUDA (sm_75) applications installed
- Weather Research and Forecasting Model (WRF 4.7.1)
- MVAPICH4-Plus 4.1 (supports EFA and Ethernet; EFA recommended for best performance)
- CUDA 12.9, NVIDIA driver 580.126.20, cuDNN 9.10.2, NCCL 2.30.7
- AWS EFA installer 1.48.0 (efa 3.0.0, libfabric 2.4.0, nv-peermem for GPU-Direct RDMA)
- Python 3.12.12 / Machine learning tools, SDKs, Frameworks etc.
- PyTorch 2.11.0+cu130, TensorFlow 2.21.0, JAX 0.10.1, Keras 3.14.1
- NVIDIA NeMo (NeMo-Run, Megatron-Core 0.17.0), NVIDIA BioNeMo (bionemo-core 2.4.5), vLLM 0.21.0, SGLang 0.5.12
- Gradio 6.15.1, Streamlit 1.58.0
- Hugging Face Transformers 5.6.0, Ray 2.55.1, W&B 0.27.0
- OpenCV 4.13.0.92, Scikit-Learn 1.9.0, XGBoost 3.3.0
- numpy 2.3.5, scipy 1.17.1, pandas 2.3.3, matplotlib 3.10.9, seaborn 0.13.2, geopandas 1.1.3, h5py 3.16.0
- JupyterLab 4.5.7 / jupyter notebook 7.5.6
- mpi4py 4.1.2
- Ollama 0.30.11
- Docker 29.6.0, Podman 4.9.3, Singularity-CE 4.4.2, NVIDIA Container Toolkit 1.19.1
- Julia 1.12.6
- Go 1.26.4
The full list of E4S applications available via the per-user Spack instance (bootstrapped on first login) is as follows:
-- linux-ubuntu24.04-aarch64 / gcc@13.3.0 --------------
- adios@1.13.1
- adios2@2.12.1
- alquimia@1.1.0
- aml@0.2.1
- amrex@26.05
- arborx@2.1
- argobots@1.2
- ascent@0.9.5
- axom@0.14.0
- boost@1.90.0
- butterflypack@3.2.0
- cabana@0.7.0
- caliper@2.14.0
- chai@2025.12.0
- chapel@2.8.0
- charliecloud@0.44
- conduit@0.9.6
- cp2k@2026.1
- cusz@0.14.0
- darshan-runtime@3.4.7
- darshan-util@3.4.7
- datatransferkit@3.1.1
- dyninst@13.0.1
- e4s-alc@1.0.3
- e4s-cl@1.0.9
- exaworks@0.1.0
- faodel@1.2108.1
- flit@2.1.0
- flux-core@0.81.0
- fpm@0.13.0
- gasnet@2025.8.0
- ginkgo@1.11.0
- globalarrays@5.8.2
- gmp@6.3.0
- gotcha@1.0.8
- gptune@5.0.0
- gromacs@2026.1
- h5bench@1.4
- hdf5@1.14.6
- hdf5-vol-async@1.7
- hdf5-vol-cache@v1.1
- hdf5-vol-log@1.4.0
- heffte@2.4.1
- hpctoolkit@2026.0.1
- hpx@1.11.0
- hypre@3.1.0
- kokkos@5.1.1
- kokkos-kernels@5.1.1
- laghos@3.1
- lammps@20250722.3
- lbann@0.104
- legion@26.03.0
- libcatalyst@2.1.0
- libceed@0.12.0
- libnrm@0.1.0
- libpressio@0.99.4
- libquo@1.4
- libunwind@1.7.2
- loki@0.1.7
- magma@2.10.0
- mercury@2.4.1
- metall@0.30
- mfem@4.9.0
- mgard@1.6.0
- mpark-variant@1.4.0
- mpifileutils@0.12
- nccmp@1.9.1.0
- nco@5.3.4
- nek5000@19.0
- nekbone@17.0
- netcdf-fortran@4.6.2
- netlib-scalapack@2.2.3
- nrm@0.1.0
- omega-h@11.0.0-scorec
- openfoam@2512
- openmpi@5.0.10
- openpmd-api@0.17.0
- papi@7.2.0
- papyrus@1.0.2
- parallel-netcdf@1.14.1
- parsec@4.0.2411
- pdt@3.25.2
- petsc@3.25.1
- phist@1.12.1
- plasma@24.8.7
- plumed@2.10.0
- precice@3.4.0
- pruners-ninja@1.0.2
- pumi@2.2.9
- py-cinemasci@1.7.9
- py-h5py@3.16.0
- py-jupyterhub@1.4.1
- py-libensemble@1.5.0
- py-petsc4py@3.25.1
- qthreads@1.18
- quantum-espresso@7.5
- raja@2025.12.2
- rempi@1.1.0
- scr@3.1.0
- slate@2025.05.28
- slepc@3.25.1
- stc@0.9.0
- strumpack@8.0.0
- sundials@7.7.0
- superlu@7.0.1
- superlu-dist@9.2.1
- swig@4.0.2-fortran
- sz@2.1.12.5
- sz3@3.2.0
- tasmanian@8.1
- tau@2.35.2
- trilinos@16.2.0
- turbine@1.3.0
- umap@2.1.1
- umpire@2025.12.0
- upcxx@2025.10.0
- veloc@1.7
- vtk-m@2.3.0
- wannier90@3.1.0
- warpx@26.04
- wps@4.5
- wrf@4.7.1
- xyce@7.10.0
- zfp@1.0.1
Additional details
Usage instructions
The 1-Click Security Group opens port 22 only so that you can access your instance via SSH using login 'ubuntu', you may change this later.
For software development and basic usage:
- Launch the ParaTools Pro for E4S (TM) AMI via 1-Click
- On the 'EC2 Launch an Instance' page pick the key pair you will use to login
- On the 'EC2 Launch an Instance' page optionally edit the network settings by pressing the edit button. Adjust the firewall rules if needed to ensure ssh access and enable Auto-assign public IP if you plan to access the instance remotely from a non-AWS IP address.
- Click 'Launch Instance'
- Find your running instance in the EC2 Instances section of the EC2 dashboard, and connect to the instance via SSH using the username ubuntu and the key pair you previously selected by picking the instance and pressing the connect button.
For more advanced usage, including launching an ParaTools Pro for E4S (TM) cluster with AWS Parallel Computing Service, please see:
Resources
Support
Vendor support
For general support questions, please email support@paratools.com
Paid support contracts and custom AMIs and computing environments are available. Please see https://paratoolspro.com/ for additional details.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Ubuntu, using AWS ParallelCluster, with over 100 HPC and AI/ML tools, an optional Amazon DCV remote desktop on the cluster head node, and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, TensorFlow, and vLLM tuned for AWS ParallelCluster, with a complete HPC software stack including numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), visualization tools (Ascent, VTK-m), performance evaluation tools (HPCToolkit, TAU), HPC applications (GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce).
This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Ubuntu, for use with Adaptive Computing's Heidi AI Cloud Supercomputer. It includes over 100 HPC and AI/ML tools, a web-based remote desktop environment, and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NIXL, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, SGLang, TensorFlow, and vLLM tuned for AWS and Heidi. The HPC stack features numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), visualization tools (ParaView, VisIt), performance evaluation tools (HPCToolkit, TAU), GPU communication libraries (NCCL, NVSHMEM), and HPC applications (CP2K, GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce).
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