Best HPC Software for Linux of 2024

Find and compare the best HPC software for Linux in 2024

Use the comparison tool below to compare the top HPC software for Linux on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

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    UberCloud Reviews

    UberCloud

    Simr (formerly UberCloud)

    3 Ratings
    Simr (formerly UberCloud) is revolutionizing the world of simulation operations with our flagship solution, Simulation Operations Automation (SimOps). Designed to streamline and automate complex simulation workflows, Simr enhances productivity, collaboration, and efficiency for engineers and scientists across various industries, including automotive, aerospace, biomedical engineering, defense, and consumer electronics. Our cloud-based infrastructure provides scalable and cost-effective solutions, eliminating the need for significant upfront investments in hardware. This ensures that our clients have access to the computational power they need, exactly when they need it, leading to reduced costs and improved operational efficiency. Simr is trusted by some of the world's leading companies, including three of the seven most successful companies globally. One of our notable success stories is BorgWarner, a Tier 1 automotive supplier that leverages Simr to automate its simulation environments, significantly enhancing their efficiency and driving innovation.
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    NVIDIA GPU-Optimized AMI Reviews
    The NVIDIA GPU Optimized AMI is a virtual image that accelerates your GPU-accelerated Machine Learning and Deep Learning workloads. This AMI allows you to spin up a GPU accelerated EC2 VM in minutes, with a preinstalled Ubuntu OS and GPU driver. Docker, NVIDIA container toolkit, and Docker are also included. This AMI provides access to NVIDIA’s NGC Catalog. It is a hub of GPU-optimized software for pulling and running performance-tuned docker containers that have been tested and certified by NVIDIA. The NGC Catalog provides free access to containerized AI and HPC applications. It also includes pre-trained AI models, AI SDKs, and other resources. This GPU-optimized AMI comes free, but you can purchase enterprise support through NVIDIA Enterprise. Scroll down to the 'Support information' section to find out how to get support for AMI.
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    Lustre Reviews

    Lustre

    OpenSFS and EOFS

    Free
    The Lustre file is an open-source parallel file system which supports many of the requirements of simulation environments for leadership class HPC. These pages are a great resource for anyone who is interested in the Lustre filesystem as a parallel system or a member of its diverse development community. The Lustre filesystem provides a POSIX compliant file system interface that can scale up to thousands of clients and petabytes in storage. It also supports hundreds of gigabytes/second of I/O bandwidth. The Lustre file system is composed of Metadata Servers, Metadata Targets, Object Storage Servers, Object Server Targets and Lustre Clients. Lustre was designed to provide a global, POSIX compliant namespace that is coherent and scalable for supercomputer platforms, as well as very large computer infrastructure. It can support hundreds or petabytes worth of data storage.
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    TrinityX Reviews

    TrinityX

    Cluster Vision

    Free
    TrinityX, an open-source cluster management system created by ClusterVision to provide 24/7 oversight of High-Performance Computing and Artificial Intelligence environments. It provides a reliable, SLA-compliant system of support, allowing users the freedom to focus on their research, while still managing complex technologies like Linux, SLURM CUDA, InfiniBand Lustre and Open OnDemand. TrinityX simplifies cluster deployment with an intuitive interface that guides users step-bystep in configuring clusters for diverse purposes such as container orchestration, HPC and InfiniBand/RDMA. The BitTorrent protocol enables rapid deployment and setup of AI/HPC Nodes. The platform offers a dashboard that provides real-time insights on cluster metrics, resource usage, and workload distribution. This allows for the identification of bottlenecks, and optimizes resource allocation.
  • 5
    Rocky Linux Reviews
    CIQ empowers people to do amazing things by providing innovative and stable software infrastructure solutions for all computing needs. From the base operating system, through containers, orchestration, provisioning, computing, and cloud applications, CIQ works with every part of the technology stack to drive solutions for customers and communities with stable, scalable, secure production environments. CIQ is the founding support and services partner of Rocky Linux, and the creator of the next generation federated computing stack.
  • 6
    Arm Forge Reviews
    You can build reliable and optimized code to achieve the best results on multiple Server or HPC architectures. This includes the latest compilers and C++ standard, as well as Intel, 64-bit Arm and AMD, OpenPOWER and Nvidia GPU hardware. Arm Forge combines Arm DDT (the leading debugger for efficient, high-performance application debugging), Arm MAP (the trusted performance profiler that provides invaluable optimization advice across native, Python, and HPC codes), and Arm Performance Reports, which provide advanced reporting capabilities. Arm DDT/Arm MAP can also be purchased as standalone products. Arm experts provide full technical support for efficient application development on Linux Server and HPC. Arm DDT is the best debugger for C++, C, and Fortran parallel applications. Arm DDT's intuitive graphical interface makes it easy to detect memory bugs at all scales and divergent behavior. This makes it the most popular debugger in academia, industry, research, and academia.
  • 7
    Intel oneAPI HPC Toolkit Reviews
    High-performance computing is the heart of AI, machine learning and deep learning applications. The Intel® oneAPI HPC Toolkit is a toolkit that allows developers to create, analyze, optimize and scale HPC applications using the most recent techniques in vectorization and multithreading, multi-node paralelization, memory optimization, and multi-node parallelization. This toolkit is an extension to the Intel(r] oneAPI Base Toolkit. It is required for full functionality. Access to the Intel(r?) Distribution for Python*, Intel(r] oneAPI DPC++/C++ C compiler, powerful data-centric library and advanced analysis tools are all included. You get everything you need to optimize, test, and build your oneAPI projects. An Intel(r] Developer Cloud account gives you 120 days access to the latest Intel®, hardware, CPUs and GPUs as well as Intel oneAPI tools, frameworks and frameworks. No software downloads. No configuration steps and no installations
  • 8
    NVIDIA Modulus Reviews
    NVIDIA Modulus, a neural network framework, combines the power of Physics in the form of governing partial differential equations (PDEs), with data to create high-fidelity surrogate models with near real-time latency. NVIDIA Modulus is a tool that can help you solve complex, nonlinear, multiphysics problems using AI. This tool provides the foundation for building physics machine learning surrogate models that combine physics and data. This framework can be applied to many domains and uses, including engineering simulations and life sciences. It can also be used to solve forward and inverse/data assimilation issues. Parameterized system representation that solves multiple scenarios in near real-time, allowing you to train once offline and infer in real-time repeatedly.
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    Amazon EC2 P4 Instances Reviews
    Amazon EC2 instances P4d deliver high performance in cloud computing for machine learning applications and high-performance computing. They offer 400 Gbps networking and are powered by NVIDIA Tensor Core GPUs. P4d instances offer up to 60% less cost for training ML models. They also provide 2.5x better performance compared to the previous generation P3 and P3dn instance. P4d instances are deployed in Amazon EC2 UltraClusters which combine high-performance computing with networking and storage. Users can scale from a few NVIDIA GPUs to thousands, depending on their project requirements. Researchers, data scientists and developers can use P4d instances to build ML models to be used in a variety of applications, including natural language processing, object classification and detection, recommendation engines, and HPC applications.
  • 10
    HPE Performance Cluster Manager Reviews
    The integrated system management solution for Linux®, high-performance computing (HPC), clusters is offered by HPE Performance Cluster Manager (HPCM). HPE Performance Cluster Manager offers complete provisioning, management and monitoring of clusters that scale up to Exascale-sized supercomputers. The software allows for fast system setup starting from bare metal, comprehensive hardware monitoring, management, software updates, power management and cluster health management. It makes scaling HPC clusters faster and more efficient, and integrates with a variety of third-party tools to manage and run workloads. HPE Performance Cluster Manager cuts down on the time and effort required to administer HPC systems. This results in lower total cost of ownership, increased productivity, and a higher return on investment.
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    NVIDIA HPC SDK Reviews
    The NVIDIA HPC Software Developer Kit (SDK), includes the proven compilers and libraries, as well as software tools that maximize developer productivity and improve the portability and performance of HPC applications. NVIDIA HPC SDK C and C++, and Fortran compilers allow GPU acceleration of HPC simulation and modeling applications using standard C++ and Fortran, OpenACC® directives and CUDA®. GPU-accelerated math libraries maximize performance for common HPC algorithms. Optimized communications libraries allow standards-based multi-GPU programming and scalable systems programming. Debugging and performance profiling tools make porting and optimizing HPC applications easier. Containerization tools allow for easy deployment on-premises and in the cloud. The HPC SDK supports NVIDIA GPUs, Arm, OpenPOWER or x86 64 CPUs running Linux.
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