Alternatives to Fuzzball

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.

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.

Develop a hybrid storage solution that seamlessly integrates with your current network-attached storage (NAS) and Azure Blob Storage. This on-premises caching appliance enhances data accessibility whether it resides in your datacenter, within Azure, or traversing a wide-area network (WAN). Comprising both software and hardware, the Microsoft Azure FXT Edge Filer offers exceptional throughput and minimal latency, designed specifically for hybrid storage environments that cater to high-performance computing (HPC) applications. Utilizing a scale-out clustering approach, it enables non-disruptive performance scaling of NAS capabilities. You can connect up to 24 FXT nodes in each cluster, allowing for an impressive expansion to millions of IOPS and several hundred GB/s speeds. When performance and scalability are critical for file-based tasks, Azure FXT Edge Filer ensures that your data remains on the quickest route to processing units. Additionally, managing your data storage becomes straightforward with Azure FXT Edge Filer, enabling you to transfer legacy data to Azure Blob Storage for easy access with minimal latency. This solution allows for a balanced approach between on-premises and cloud storage, ensuring optimal efficiency in data management while adapting to evolving business needs. Furthermore, this hybrid model supports organizations in maximizing their existing infrastructure investments while leveraging the benefits of cloud technology.

Bright Cluster Manager offers a variety of machine learning frameworks including Torch, Tensorflow and Tensorflow to simplify your deep-learning projects. Bright offers a selection the most popular Machine Learning libraries that can be used to access datasets. These include MLPython and NVIDIA CUDA Deep Neural Network Library (cuDNN), Deep Learning GPU Trainer System (DIGITS), CaffeOnSpark (a Spark package that allows deep learning), and MLPython. Bright makes it easy to find, configure, and deploy all the necessary components to run these deep learning libraries and frameworks. There are over 400MB of Python modules to support machine learning packages. We also include the NVIDIA hardware drivers and CUDA (parallel computer platform API) drivers, CUB(CUDA building blocks), NCCL (library standard collective communication routines).

AWS High Performance Computing (HPC) services enable users to run extensive simulations and deep learning tasks in the cloud, offering nearly limitless computing power, advanced file systems, and high-speed networking capabilities. This comprehensive set of services fosters innovation by providing a diverse array of cloud-based resources, such as machine learning and analytics tools, which facilitate swift design and evaluation of new products. Users can achieve peak operational efficiency thanks to the on-demand nature of these computing resources, allowing them to concentrate on intricate problem-solving without the limitations of conventional infrastructure. AWS HPC offerings feature the Elastic Fabric Adapter (EFA) for optimized low-latency and high-bandwidth networking, AWS Batch for efficient scaling of computing tasks, AWS ParallelCluster for easy cluster setup, and Amazon FSx for delivering high-performance file systems. Collectively, these services create a flexible and scalable ecosystem that is well-suited for a variety of HPC workloads, empowering organizations to push the boundaries of what’s possible in their respective fields. As a result, users can experience greatly enhanced performance and productivity in their computational endeavors.

AWS Parallel Computing Service (AWS PCS) is a fully managed service designed to facilitate the execution and scaling of high-performance computing tasks while also aiding in the development of scientific and engineering models using Slurm on AWS. This service allows users to create comprehensive and adaptable environments that seamlessly combine computing, storage, networking, and visualization tools, enabling them to concentrate on their research and innovative projects without the hassle of managing the underlying infrastructure. With features like automated updates and integrated observability, AWS PCS significantly improves the operations and upkeep of computing clusters. Users can easily construct and launch scalable, dependable, and secure HPC clusters via the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDK. The versatility of the service supports a wide range of applications, including tightly coupled workloads such as computer-aided engineering, high-throughput computing for tasks like genomics analysis, GPU-accelerated computing, and specialized silicon solutions like AWS Trainium and AWS Inferentia. Overall, AWS PCS empowers researchers and engineers to harness advanced computing capabilities without needing to worry about the complexities of infrastructure setup and maintenance.

TotalView debugging software offers essential tools designed to expedite the debugging, analysis, and scaling of high-performance computing (HPC) applications. This software adeptly handles highly dynamic, parallel, and multicore applications that can operate on a wide range of hardware, from personal computers to powerful supercomputers. By utilizing TotalView, developers can enhance the efficiency of HPC development, improve the quality of their code, and reduce the time needed to bring products to market through its advanced capabilities for rapid fault isolation, superior memory optimization, and dynamic visualization. It allows users to debug thousands of threads and processes simultaneously, making it an ideal solution for multicore and parallel computing environments. TotalView equips developers with an unparalleled set of tools that provide detailed control over thread execution and processes, while also offering extensive insights into program states and data, ensuring a smoother debugging experience. With these comprehensive features, TotalView stands out as a vital resource for those engaged in high-performance computing.

Amazon EC2 P4d instances are designed for optimal performance in machine learning training and high-performance computing (HPC) applications within the cloud environment. Equipped with NVIDIA A100 Tensor Core GPUs, these instances provide exceptional throughput and low-latency networking capabilities, boasting 400 Gbps instance networking. P4d instances are remarkably cost-effective, offering up to a 60% reduction in expenses for training machine learning models, while also delivering an impressive 2.5 times better performance for deep learning tasks compared to the older P3 and P3dn models. They are deployed within expansive clusters known as Amazon EC2 UltraClusters, which allow for the seamless integration of high-performance computing, networking, and storage resources. This flexibility enables users to scale their operations from a handful to thousands of NVIDIA A100 GPUs depending on their specific project requirements. Researchers, data scientists, and developers can leverage P4d instances to train machine learning models for diverse applications, including natural language processing, object detection and classification, and recommendation systems, in addition to executing HPC tasks such as pharmaceutical discovery and other complex computations. These capabilities collectively empower teams to innovate and accelerate their projects with greater efficiency and effectiveness.

Qlustar presents an all-encompassing full-stack solution that simplifies the setup, management, and scaling of clusters while maintaining control and performance. It enhances your HPC, AI, and storage infrastructures with exceptional ease and powerful features. The journey begins with a bare-metal installation using the Qlustar installer, followed by effortless cluster operations that encompass every aspect of management. Experience unparalleled simplicity and efficiency in both establishing and overseeing your clusters. Designed with scalability in mind, it adeptly handles even the most intricate workloads with ease. Its optimization for speed, reliability, and resource efficiency makes it ideal for demanding environments. You can upgrade your operating system or handle security patches without requiring reinstallations, ensuring minimal disruption. Regular and dependable updates safeguard your clusters against potential vulnerabilities, contributing to their overall security. Qlustar maximizes your computing capabilities, ensuring peak efficiency for high-performance computing settings. Additionally, its robust workload management, built-in high availability features, and user-friendly interface provide a streamlined experience, making operations smoother than ever before. This comprehensive approach ensures that your computing infrastructure remains resilient and adaptable to changing needs.

The Nimbix Supercomputing Suite offers a diverse and secure range of high-performance computing (HPC) solutions available as a service. This innovative model enables users to tap into a comprehensive array of HPC and supercomputing resources, spanning from hardware options to bare metal-as-a-service, facilitating the widespread availability of advanced computing capabilities across both public and private data centers. Through the Nimbix Supercomputing Suite, users gain access to the HyperHub Application Marketplace, which features an extensive selection of over 1,000 applications and workflows designed for high performance. By utilizing dedicated BullSequana HPC servers as bare metal-as-a-service, clients can enjoy superior infrastructure along with the flexibility of on-demand scalability, convenience, and agility. Additionally, the federated supercomputing-as-a-service provides a centralized service console, enabling efficient management of all computing zones and regions within a public or private HPC, AI, and supercomputing federation, thereby streamlining operations and enhancing productivity. This comprehensive suite empowers organizations to drive innovation and optimize performance across various computational tasks.

AWS ParallelCluster is a free, open-source tool designed for efficient management and deployment of High-Performance Computing (HPC) clusters within the AWS environment. It streamlines the configuration of essential components such as compute nodes, shared filesystems, and job schedulers, while accommodating various instance types and job submission queues. Users have the flexibility to engage with ParallelCluster using a graphical user interface, command-line interface, or API, which allows for customizable cluster setups and oversight. The tool also works seamlessly with job schedulers like AWS Batch and Slurm, making it easier to transition existing HPC workloads to the cloud with minimal adjustments. Users incur no additional costs for the tool itself, only paying for the AWS resources their applications utilize. With AWS ParallelCluster, users can effectively manage their computing needs through a straightforward text file that allows for the modeling, provisioning, and dynamic scaling of necessary resources in a secure and automated fashion. This ease of use significantly enhances productivity and optimizes resource allocation for various computational tasks.

Accelerate computational tasks such as those found in machine learning and high-performance computing (HPC) with a diverse array of GPUs suited for various performance levels and budget constraints. With adaptable pricing and customizable machines, you can fine-tune your setup to enhance your workload efficiency. Google Cloud offers high-performance GPUs ideal for machine learning, scientific analyses, and 3D rendering. The selection includes NVIDIA K80, P100, P4, T4, V100, and A100 GPUs, providing a spectrum of computing options tailored to meet different cost and performance requirements. You can effectively balance processor power, memory capacity, high-speed storage, and up to eight GPUs per instance to suit your specific workload needs. Enjoy the advantage of per-second billing, ensuring you only pay for the resources consumed during usage. Leverage GPU capabilities on Google Cloud Platform, where you benefit from cutting-edge storage, networking, and data analytics solutions. Compute Engine allows you to easily integrate GPUs into your virtual machine instances, offering an efficient way to enhance processing power. Explore the potential uses of GPUs and discover the various types of GPU hardware available to elevate your computational projects.

Amazon S3 Express One Zone is designed as a high-performance storage class that operates within a single Availability Zone, ensuring reliable access to frequently used data and meeting the demands of latency-sensitive applications with single-digit millisecond response times. It boasts data retrieval speeds that can be up to 10 times quicker, alongside request costs that can be reduced by as much as 50% compared to the S3 Standard class. Users have the flexibility to choose a particular AWS Availability Zone in an AWS Region for their data, which enables the co-location of storage and computing resources, ultimately enhancing performance and reducing compute expenses while expediting workloads. The data is managed within a specialized bucket type known as an S3 directory bucket, which can handle hundreds of thousands of requests every second efficiently. Furthermore, S3 Express One Zone can seamlessly integrate with services like Amazon SageMaker Model Training, Amazon Athena, Amazon EMR, and AWS Glue Data Catalog, thereby speeding up both machine learning and analytical tasks. This combination of features makes S3 Express One Zone an attractive option for businesses looking to optimize their data management and processing capabilities.

TrinityX is a cluster management solution that is open source and developed by ClusterVision, aimed at ensuring continuous monitoring for environments focused on High-Performance Computing (HPC) and Artificial Intelligence (AI). It delivers a robust support system that adheres to service level agreements (SLAs), enabling researchers to concentrate on their work without the burden of managing intricate technologies such as Linux, SLURM, CUDA, InfiniBand, Lustre, and Open OnDemand. By providing an easy-to-use interface, TrinityX simplifies the process of cluster setup, guiding users through each phase to configure clusters for various applications including container orchestration, conventional HPC, and InfiniBand/RDMA configurations. Utilizing the BitTorrent protocol, it facilitates the swift deployment of AI and HPC nodes, allowing for configurations to be completed in mere minutes. Additionally, the platform boasts a detailed dashboard that presents real-time data on cluster performance metrics, resource usage, and workload distribution, which helps users quickly identify potential issues and optimize resource distribution effectively. This empowers teams to make informed decisions that enhance productivity and operational efficiency within their computational environments.

Amazon EC2 UltraClusters allow for the scaling of thousands of GPUs or specialized machine learning accelerators like AWS Trainium, granting users immediate access to supercomputing-level performance. This service opens the door to supercomputing for developers involved in machine learning, generative AI, and high-performance computing, all through a straightforward pay-as-you-go pricing structure that eliminates the need for initial setup or ongoing maintenance expenses. Comprising thousands of accelerated EC2 instances placed within a specific AWS Availability Zone, UltraClusters utilize Elastic Fabric Adapter (EFA) networking within a petabit-scale nonblocking network. Such an architecture not only ensures high-performance networking but also facilitates access to Amazon FSx for Lustre, a fully managed shared storage solution based on a high-performance parallel file system that enables swift processing of large datasets with sub-millisecond latency. Furthermore, EC2 UltraClusters enhance scale-out capabilities for distributed machine learning training and tightly integrated HPC tasks, significantly decreasing training durations while maximizing efficiency. This transformative technology is paving the way for groundbreaking advancements in various computational fields.

The NVIDIA DGX Cloud provides an AI infrastructure as a service that simplifies the deployment of large-scale AI models and accelerates innovation. By offering a comprehensive suite of tools for machine learning, deep learning, and HPC, this platform enables organizations to run their AI workloads efficiently on the cloud. With seamless integration into major cloud services, it offers the scalability, performance, and flexibility necessary for tackling complex AI challenges, all while eliminating the need for managing on-premise hardware.

The NVIDIA HPC Software Development Kit (SDK) offers a comprehensive suite of reliable compilers, libraries, and software tools that are crucial for enhancing developer efficiency as well as the performance and adaptability of HPC applications. This SDK includes C, C++, and Fortran compilers that facilitate GPU acceleration for HPC modeling and simulation applications through standard C++ and Fortran, as well as OpenACC® directives and CUDA®. Additionally, GPU-accelerated mathematical libraries boost the efficiency of widely used HPC algorithms, while optimized communication libraries support standards-based multi-GPU and scalable systems programming. The inclusion of performance profiling and debugging tools streamlines the process of porting and optimizing HPC applications, and containerization tools ensure straightforward deployment whether on-premises or in cloud environments. Furthermore, with compatibility for NVIDIA GPUs and various CPU architectures like Arm, OpenPOWER, or x86-64 running on Linux, the HPC SDK equips developers with all the necessary resources to create high-performance GPU-accelerated HPC applications effectively. Ultimately, this robust toolkit is indispensable for anyone looking to push the boundaries of high-performance computing.

Arm Allinea Studio is a comprehensive set of tools designed for the development of server and high-performance computing (HPC) applications specifically on Arm architectures. This suite includes compilers and libraries tailored for Arm, as well as tools for debugging and optimization. Among its offerings, the Arm Performance Libraries deliver optimized standard core mathematical libraries that enhance the performance of HPC applications running on Arm processors. These libraries feature routines accessible through both Fortran and C interfaces. Additionally, the Arm Performance Libraries incorporate OpenMP, ensuring a wide range of support across various BLAS, LAPACK, FFT, and sparse routines, ultimately aimed at maximizing performance in multi-processor environments. With these tools, developers can efficiently harness the full potential of Arm-based platforms for their computational needs.

Kombyne™ represents a cutting-edge Software as a Service (SaaS) tool designed for high-performance computing (HPC) workflows, originally tailored for clients in sectors such as defense, automotive, aerospace, and academic research. This platform empowers users to access a diverse array of workflow solutions specifically for HPC computational fluid dynamics (CFD) tasks, encompassing features like on-the-fly extract generation, rendering capabilities, and simulation steering options. Users can benefit from interactive monitoring and control functionalities, all while ensuring minimal disruption to simulations and eliminating reliance on VTK. By employing extract workflows, the necessity for handling large files is significantly reduced, allowing for real-time visualization. The system incorporates an in-transit workflow that utilizes a distinct process to swiftly receive data from the solver code, enabling visualization and analysis without hindering the operation of the running solver. This specialized process, referred to as an endpoint, facilitates the direct output of extracts, cutting planes, or point samples useful for data science, in addition to rendering images. Furthermore, the Endpoint serves as a conduit to widely-used visualization software, enhancing the overall usability and integration of the tool within various workflows. With its versatile features and ease of use, Kombyne™ is set to revolutionize the way HPC tasks are managed and executed across multiple industries.

The NVIDIA GPU-Optimized AMI serves as a virtual machine image designed to enhance your GPU-accelerated workloads in Machine Learning, Deep Learning, Data Science, and High-Performance Computing (HPC). By utilizing this AMI, you can quickly launch a GPU-accelerated EC2 virtual machine instance, complete with a pre-installed Ubuntu operating system, GPU driver, Docker, and the NVIDIA container toolkit, all within a matter of minutes. This AMI simplifies access to NVIDIA's NGC Catalog, which acts as a central hub for GPU-optimized software, enabling users to easily pull and run performance-tuned, thoroughly tested, and NVIDIA-certified Docker containers. The NGC catalog offers complimentary access to a variety of containerized applications for AI, Data Science, and HPC, along with pre-trained models, AI SDKs, and additional resources, allowing data scientists, developers, and researchers to concentrate on creating and deploying innovative solutions. Additionally, this GPU-optimized AMI is available at no charge, with an option for users to purchase enterprise support through NVIDIA AI Enterprise. For further details on obtaining support for this AMI, please refer to the section labeled 'Support Information' below. Moreover, leveraging this AMI can significantly streamline the development process for projects requiring intensive computational resources.

Azure offers high-performance computing (HPC) solutions that drive innovative breakthroughs, tackle intricate challenges, and enhance your resource-heavy tasks. You can create and execute your most demanding applications in the cloud with a comprehensive solution specifically designed for HPC. Experience the benefits of supercomputing capabilities, seamless interoperability, and nearly limitless scalability for compute-heavy tasks through Azure Virtual Machines. Enhance your decision-making processes and advance next-generation AI applications using Azure's top-tier AI and analytics services. Additionally, protect your data and applications while simplifying compliance through robust, multilayered security measures and confidential computing features. This powerful combination ensures that organizations can achieve their computational goals with confidence and efficiency.

Moab®, HPC Suite automates the management, monitoring, reporting, and scheduling of large-scale HPC workloads. Its intelligence engine, which is patent-pending, uses multi-dimensional policies to optimize workload start times and run time on different resources. These policies balance high utilization goals and throughput with competing workload priorities, SLA requirements, and thus accomplish more work in less time and in a better priority order. Moab HPC Suite maximizes the value and use of HPC systems, while reducing complexity and management costs.

Create dependable and optimized code that delivers accurate results across various Server and HPC architectures, utilizing the latest compilers and C++ standards tailored for Intel, 64-bit Arm, AMD, OpenPOWER, and Nvidia GPU platforms. Arm Forge integrates Arm DDT, a premier debugger designed to streamline the debugging process of high-performance applications, with Arm MAP, a respected performance profiler offering essential optimization insights for both native and Python HPC applications, along with Arm Performance Reports that provide sophisticated reporting features. Both Arm DDT and Arm MAP can also be used as independent products, allowing flexibility in application development. This package ensures efficient Linux Server and HPC development while offering comprehensive technical support from Arm specialists. Arm DDT stands out as the preferred debugger for C++, C, or Fortran applications that are parallel or threaded, whether they run on CPUs or GPUs. With its powerful and user-friendly graphical interface, Arm DDT enables users to swiftly identify memory errors and divergent behaviors at any scale, solidifying its reputation as the leading debugger in the realms of research, industry, and academia, making it an invaluable tool for developers. Additionally, its rich feature set fosters an environment conducive to innovation and performance enhancement.

High-performance computing (HPC) serves as a fundamental element for applications in AI, machine learning, and deep learning. The Intel® oneAPI HPC Toolkit (HPC Kit) equips developers with essential tools to create, analyze, enhance, and expand HPC applications by utilizing the most advanced methods in vectorization, multithreading, multi-node parallelization, and memory management. This toolkit is an essential complement to the Intel® oneAPI Base Toolkit, which is necessary to unlock its complete capabilities. Additionally, it provides users with access to the Intel® Distribution for Python*, the Intel® oneAPI DPC++/C++ compiler, a suite of robust data-centric libraries, and sophisticated analysis tools. You can obtain everything needed to construct, evaluate, and refine your oneAPI projects at no cost. By signing up for an Intel® Developer Cloud account, you gain 120 days of access to the latest Intel® hardware—including CPUs, GPUs, FPGAs—and the full suite of Intel oneAPI tools and frameworks. This seamless experience requires no software downloads, no configuration processes, and no installations, making it incredibly user-friendly for developers at all levels.

Warewulf is a cutting-edge cluster management and provisioning solution that has led the way in stateless node management for more than twenty years. This innovative system facilitates the deployment of containers directly onto bare metal hardware at an impressive scale, accommodating anywhere from a handful to tens of thousands of computing units while preserving an easy-to-use and adaptable framework. The platform offers extensibility, which empowers users to tailor default functionalities and node images to meet specific clustering needs. Additionally, Warewulf endorses stateless provisioning that incorporates SELinux, along with per-node asset key-based provisioning and access controls, thereby ensuring secure deployment environments. With its minimal system requirements, Warewulf is designed for straightforward optimization, customization, and integration, making it suitable for a wide range of industries. Backed by OpenHPC and a global community of contributors, Warewulf has established itself as a prominent HPC cluster platform applied across multiple sectors. Its user-friendly features not only simplify initial setup but also enhance the overall adaptability, making it an ideal choice for organizations seeking efficient cluster management solutions.

The Lustre file system is a parallel, open-source file system designed to cater to the demanding requirements of high-performance computing (HPC) simulation environments often found in leadership class facilities. Whether you are part of our vibrant development community or evaluating Lustre as a potential parallel file system option, you will find extensive resources and support available to aid you. Offering a POSIX-compliant interface, the Lustre file system can efficiently scale to accommodate thousands of clients, manage petabytes of data, and deliver impressive I/O bandwidths exceeding hundreds of gigabytes per second. Its architecture includes essential components such as Metadata Servers (MDS), Metadata Targets (MDT), Object Storage Servers (OSS), Object Server Targets (OST), and Lustre clients. Lustre is specifically engineered to establish a unified, global POSIX-compliant namespace suited for massive computing infrastructures, including some of the largest supercomputing platforms in existence. With its capability to handle hundreds of petabytes of data storage, Lustre stands out as a robust solution for organizations looking to manage extensive datasets effectively. Its versatility and scalability make it a preferable choice for a wide range of applications in scientific research and data-intensive computing.

There's no requirement to modify your coding practices or the methods you use to develop your projects. You can conduct profiling for applications that operate on multiple servers and involve various processes, providing clear insights into potential bottlenecks related to I/O, computational tasks, threading, or multi-process operations. You'll gain a profound understanding of the specific types of processor instructions that impact your overall performance. Additionally, you can monitor memory usage over time, allowing you to identify peak usage points and fluctuations throughout the entire memory landscape. Arm MAP stands out as a uniquely scalable profiler with low overhead, available both as an independent tool and as part of the comprehensive Arm Forge debugging and profiling suite. It is designed to assist developers of server and high-performance computing (HPC) software in speeding up their applications by pinpointing the root causes of sluggish performance. This tool is versatile enough to be employed on everything from multicore Linux workstations to advanced supercomputers. You have the option to profile realistic scenarios that matter the most to you while typically incurring less than 5% in runtime overhead. The user interface is interactive, fostering clarity and ease of use, making it well-suited for both developers and computational scientists alike, enhancing their productivity and efficiency.

Covalent's innovative serverless HPC framework facilitates seamless job scaling from personal laptops to high-performance computing and cloud environments. Designed for computational scientists, AI/ML developers, and those requiring access to limited or costly computing resources like quantum computers, HPC clusters, and GPU arrays, Covalent serves as a Pythonic workflow solution. Researchers can execute complex computational tasks on cutting-edge hardware, including quantum systems or serverless HPC clusters, with just a single line of code. The most recent update to Covalent introduces two new feature sets along with three significant improvements. Staying true to its modular design, Covalent now empowers users to create custom pre- and post-hooks for electrons, enhancing the platform's versatility for tasks ranging from configuring remote environments (via DepsPip) to executing tailored functions. This flexibility opens up a wide array of possibilities for researchers and developers alike, making their workflows more efficient and adaptable.

Design, oversee, operate, and enhance high-performance computing (HPC) and large-scale compute clusters seamlessly. Implement comprehensive clusters and additional resources, encompassing task schedulers, computational virtual machines, storage solutions, networking capabilities, and caching systems. Tailor and refine clusters with sophisticated policy and governance tools, which include cost management, integration with Active Directory, as well as monitoring and reporting functionalities. Utilize your existing job scheduler and applications without any necessary changes. Empower administrators with complete authority over job execution permissions for users, in addition to determining the locations and associated costs for running jobs. Benefit from integrated autoscaling and proven reference architectures suitable for diverse HPC workloads across various sectors. CycleCloud accommodates any job scheduler or software environment, whether it's proprietary, in-house solutions or open-source, third-party, and commercial software. As your requirements for resources shift and grow, your cluster must adapt accordingly. With scheduler-aware autoscaling, you can ensure that your resources align perfectly with your workload needs while remaining flexible to future changes. This adaptability is crucial for maintaining efficiency and performance in a rapidly evolving technological landscape.

HPE Performance Cluster Manager (HPCM) offers a cohesive system management solution tailored for Linux®-based high-performance computing (HPC) clusters. This software facilitates comprehensive provisioning, management, and monitoring capabilities for clusters that can extend to Exascale-sized supercomputers. HPCM streamlines the initial setup from bare-metal, provides extensive hardware monitoring and management options, oversees image management, handles software updates, manages power efficiently, and ensures overall cluster health. Moreover, it simplifies the scaling process for HPC clusters and integrates seamlessly with numerous third-party tools to enhance workload management. By employing HPE Performance Cluster Manager, organizations can significantly reduce the administrative burden associated with HPC systems, ultimately leading to lowered total ownership costs and enhanced productivity, all while maximizing the return on their hardware investments. As a result, HPCM not only fosters operational efficiency but also supports organizations in achieving their computational goals effectively.

The Ansys HPC software suite allows users to leverage modern multicore processors to conduct a greater number of simulations in a shorter timeframe. These simulations can achieve unprecedented levels of complexity, size, and accuracy thanks to high-performance computing (HPC) capabilities. Ansys provides a range of HPC licensing options that enable scalability, accommodating everything from single-user setups for basic parallel processing to extensive configurations that support nearly limitless parallel processing power. For larger teams, Ansys ensures the ability to execute highly scalable, multiple parallel processing simulations to tackle the most demanding projects. In addition to its parallel computing capabilities, Ansys also delivers parametric computing solutions, allowing for a deeper exploration of various design parameters—including dimensions, weight, shape, materials, and mechanical properties—during the early stages of product development. This comprehensive approach not only enhances simulation efficiency but also significantly optimizes the design process.

The Elastic Fabric Adapter (EFA) serves as a specialized network interface for Amazon EC2 instances, allowing users to efficiently run applications that demand high inter-node communication at scale within the AWS environment. By utilizing a custom-designed operating system (OS) that circumvents traditional hardware interfaces, EFA significantly boosts the performance of communications between instances, which is essential for effectively scaling such applications. This technology facilitates the scaling of High-Performance Computing (HPC) applications that utilize the Message Passing Interface (MPI) and Machine Learning (ML) applications that rely on the NVIDIA Collective Communications Library (NCCL) to thousands of CPUs or GPUs. Consequently, users can achieve the same high application performance found in on-premises HPC clusters while benefiting from the flexible and on-demand nature of the AWS cloud infrastructure. EFA can be activated as an optional feature for EC2 networking without incurring any extra charges, making it accessible for a wide range of use cases. Additionally, it seamlessly integrates with the most popular interfaces, APIs, and libraries for inter-node communication needs, enhancing its utility for diverse applications.

NVIDIA GPU Cloud (NGC) serves as a cloud platform that harnesses GPU acceleration for deep learning and scientific computations. It offers a comprehensive catalog of fully integrated containers for deep learning frameworks designed to optimize performance on NVIDIA GPUs, whether in single or multi-GPU setups. Additionally, the NVIDIA train, adapt, and optimize (TAO) platform streamlines the process of developing enterprise AI applications by facilitating quick model adaptation and refinement. Through a user-friendly guided workflow, organizations can fine-tune pre-trained models with their unique datasets, enabling them to create precise AI models in mere hours instead of the traditional months, thereby reducing the necessity for extensive training periods and specialized AI knowledge. If you're eager to dive into the world of containers and models on NGC, you’ve found the ideal starting point. Furthermore, NGC's Private Registries empower users to securely manage and deploy their proprietary assets, enhancing their AI development journey.

Amazon's Elastic Compute Cloud (EC2) offers P5 instances that utilize NVIDIA H100 Tensor Core GPUs, alongside P5e and P5en instances featuring NVIDIA H200 Tensor Core GPUs, ensuring unmatched performance for deep learning and high-performance computing tasks. With these advanced instances, you can reduce the time to achieve results by as much as four times compared to earlier GPU-based EC2 offerings, while also cutting ML model training costs by up to 40%. This capability enables faster iteration on solutions, allowing businesses to reach the market more efficiently. P5, P5e, and P5en instances are ideal for training and deploying sophisticated large language models and diffusion models that drive the most intensive generative AI applications, which encompass areas like question-answering, code generation, video and image creation, and speech recognition. Furthermore, these instances can also support large-scale deployment of high-performance computing applications, facilitating advancements in fields such as pharmaceutical discovery, ultimately transforming how research and development are conducted in the industry.

The Intel® Tiber™ AI Cloud serves as a robust platform tailored to efficiently scale artificial intelligence workloads through cutting-edge computing capabilities. Featuring specialized AI hardware, including the Intel Gaudi AI Processor and Max Series GPUs, it enhances the processes of model training, inference, and deployment. Aimed at enterprise-level applications, this cloud offering allows developers to create and refine models using well-known libraries such as PyTorch. Additionally, with a variety of deployment choices, secure private cloud options, and dedicated expert assistance, Intel Tiber™ guarantees smooth integration and rapid deployment while boosting model performance significantly. This comprehensive solution is ideal for organizations looking to harness the full potential of AI technologies.

Utilizing the distinctive and inherently dynamic Lattice Boltzmann-based physics, the PowerFLOW CFD solution conducts simulations that effectively replicate real-world scenarios. With the PowerFLOW suite, engineers can assess product performance at the early stages of design, before any prototypes are constructed—this is when alterations can have the most substantial effects on both design and budget. The PowerFLOW system seamlessly imports intricate model geometries and conducts aerodynamic, aeroacoustic, and thermal management simulations with high accuracy and efficiency. By automating domain discretization and turbulence modeling along with wall treatment, it removes the need for manual volume meshing and boundary layer meshing. Users can confidently execute PowerFLOW simulations using a large number of compute cores on widely utilized High Performance Computing (HPC) platforms, enhancing productivity and reliability in the simulation process. This capability not only accelerates product development timelines but also ensures that potential issues are identified and addressed early in the design phase.

Intel presents an extensive array of development tools specifically designed for working with Altera FPGAs, CPLDs, and SoC FPGAs, addressing the needs of hardware engineers, software developers, and system architects alike. The Quartus Prime Design Software acts as a versatile platform that integrates all essential functionalities required for the design of FPGAs, SoC FPGAs, and CPLDs, covering aspects such as synthesis, optimization, verification, and simulation. To support high-level design, Intel offers a set of tools including the Altera FPGA Add-on for the oneAPI Base Toolkit, DSP Builder, the High-Level Synthesis (HLS) Compiler, and the P4 Suite for FPGA, which enhance the development process in fields like digital signal processing and high-level synthesis. Additionally, embedded developers can take advantage of Nios V soft embedded processors along with a variety of embedded design tools such as the Ashling RiscFree IDE and Arm Development Studio (DS) tailored for Altera SoC FPGAs, effectively simplifying the software development process for embedded systems. These resources ensure that developers can create optimized solutions efficiently across different application domains.

The convergence of high-performance computing (HPC) and machine learning is placing unprecedented requirements on storage solutions, as the input/output demands of these two distinct workloads diverge significantly. This shift is occurring at this very moment, with a recent analysis from the independent firm Intersect360 revealing that a striking 63% of current HPC users are actively implementing machine learning applications. Furthermore, Hyperion Research projects that, if trends continue, public sector organizations and enterprises will see HPC storage expenditures increase at a rate 57% faster than HPC compute investments over the next three years. Reflecting on this, Seymour Cray famously stated, "Anyone can build a fast CPU; the trick is to build a fast system." In the realm of HPC and AI, while creating fast file storage may seem straightforward, the true challenge lies in developing a storage system that is not only quick but also economically viable and capable of scaling effectively. We accomplish this by integrating top-tier parallel file systems into HPE's parallel storage solutions, ensuring that cost efficiency is a fundamental aspect of our approach. This strategy not only meets the current demands of users but also positions us well for future growth.

Establish your Kubernetes infrastructure and utilize KubeGrid for the seamless deployment, monitoring, and optimization of potentially thousands of clusters. KubeGrid streamlines the complete lifecycle management of Kubernetes across both on-premises and cloud environments, allowing developers to effortlessly deploy, manage, and update numerous clusters. As a Platform as Code solution, KubeGrid enables you to declaratively specify all your Kubernetes needs in a code format, covering everything from your on-prem or cloud infrastructure to the specifics of clusters and autoscaling policies, with KubeGrid handling the deployment and management automatically. While most infrastructure-as-code solutions focus solely on provisioning, KubeGrid enhances the experience by automating Day 2 operations, including monitoring infrastructure, managing failovers for unhealthy nodes, and updating both clusters and their operating systems. Thanks to its innovative approach, Kubernetes excels in the automated provisioning of pods, ensuring efficient resource utilization across your infrastructure. By adopting KubeGrid, you transform the complexities of Kubernetes management into a streamlined and efficient process.

In the last twenty years, there have been significant advancements in software technologies, and high-performance computing (HPC) has progressed exponentially. However, our capacity to interpret simulation results has not experienced a similar evolution. Traditional methods of visualizing data, such as creating plots and animations, fail to keep pace when faced with extremely large multi-billion cell meshes or extensive simulations involving tens of thousands of timesteps. The process of evaluating solutions can be greatly expedited by generating features and quantitative metrics through techniques like eigen analysis or machine learning. Furthermore, the user-friendly FieldView desktop software is seamlessly integrated with the robust capabilities of the VisIt Prime backend, enhancing the overall analysis experience. This integration allows for a more efficient workflow, enabling researchers to focus on interpreting results rather than being bogged down by outdated visualization methods.

Cloud cost reductions of 30%, provisioning 150x faster, closing security holes, and deployment of hybrid-cloud automation in record times are some of the benefits. Morpheus provides enterprise agility, control and efficiency through its self-service engine. Quickly enable private cloud access on-prem, centralize public cloud access, orchestrate change using cost analytics, governance policies, and automation. Manage public clouds, create private clouds, consolidate Kubernetes deployments, and manage public clouds. Provision applications from an on-demand catalog, API/CLI, ITSM, or infrastructure-as-code. Simplify authentication, access controls, policies, and security management. Automate lifecycles, streamline workflows, and simplify day-to-day tasks. Inventory brownfields, rightsize resource, track cloud spend, and centralize visibility.

Intel® Tiber™ AI Studio serves as an all-encompassing machine learning operating system designed to streamline and unify the development of artificial intelligence. This robust platform accommodates a diverse array of AI workloads and features a hybrid multi-cloud infrastructure that enhances the speed of ML pipeline creation, model training, and deployment processes. By incorporating native Kubernetes orchestration and a meta-scheduler, Tiber™ AI Studio delivers unparalleled flexibility for managing both on-premises and cloud resources. Furthermore, its scalable MLOps framework empowers data scientists to seamlessly experiment, collaborate, and automate their machine learning workflows, all while promoting efficient and cost-effective resource utilization. This innovative approach not only boosts productivity but also fosters a collaborative environment for teams working on AI projects.

A versatile and straightforward workload orchestrator designed to deploy and oversee both containerized and non-containerized applications seamlessly across on-premises and cloud environments at scale. This efficient tool comes as a single 35MB binary that effortlessly fits into your existing infrastructure. It provides an easy operational experience whether on-prem or in the cloud, maintaining minimal overhead. Capable of orchestrating various types of applications—not limited to just containers—it offers top-notch support for Docker, Windows, Java, VMs, and more. By introducing orchestration advantages, it helps enhance existing services. Users can achieve zero downtime deployments, increased resilience, and improved resource utilization without the need for containerization. A single command allows for multi-region, multi-cloud federation, enabling global application deployment to any region using Nomad as a cohesive control plane. This results in a streamlined workflow for deploying applications to either bare metal or cloud environments. Additionally, Nomad facilitates the development of multi-cloud applications with remarkable ease and integrates smoothly with Terraform, Consul, and Vault for efficient provisioning, service networking, and secrets management, making it an indispensable tool in modern application management.

Concierto.Cloud, a multi-cloud infrastructure management platform, offers high-level automation to manage cloud and on-premise infrastructures from one location. Automation can increase speed, efficiency, lower costs, and scale. You can manage your cloud and on-prem environments. Respond to incidents, requests, and changes from one place. Concierto.Cloud enables you to manage multiple cloud instances simultaneously using a single interface. Advanced automation allows you to trigger policy and rule-based execution. Concierto.Cloud's dynamic CMDB and ITSM capabilities, as well as cloud native tools, allows proactive service management. Maximize asset utilization across all clouds and on prem through 3600 visibility.

To thrive in today's competitive digital landscape, enterprises must automate a wide array of applications, platforms, and technologies to effectively deliver services. Service Orchestration and Automation Platforms play a crucial role in scaling IT operations and maximizing the benefits of automation; they enable the management of intricate workflows that span various platforms, including ERP systems and business applications, from mainframes to microservices across multi-cloud environments. Additionally, it is vital to optimize big data pipelines, allowing data scientists to utilize self-service options while ensuring extensive scalability and robust governance over data flows. Organizations must also deliver compute, networking, and storage resources both on-premises and in the cloud to support development and business users. Automic Automation offers the agility, speed, and reliability necessary for successful digital business automation, providing a unified platform that centralizes orchestration and automation functions to facilitate and expedite digital transformation efforts effectively. With these capabilities, businesses can seamlessly adapt to changing demands while maintaining operational efficiency.

Enjoy a unified testing experience across various test types. You can utilize the same test scripts regardless of whether you're assessing a web application on numerous browser, operating system, and device combinations, checking the functionality of your APIs, or conducting extensive load tests. Our enterprise-ready SaaS platform, hosted in the cloud by Testable, enables you to execute tests either in the cloud or on-premises with your preferred open-source tools, while we manage the test execution, real-time reporting, detailed analysis, and secure storage in the cloud. Additionally, you have the option to securely deploy our testing platform on your own infrastructure, safeguarded behind your firewall. With modern, scalable, and flexible packaging options, including a convenient one-click Kubernetes Helm package, you can run functional tests across multiple browsers, OS, and devices in a single test run. Furthermore, you will have access to a real-time report that showcases live interactive sessions, videos for each virtual user, screenshots, assertions, performance metrics, trend analysis, and a wealth of additional insights to enhance your testing process. This comprehensive approach ensures that you have everything you need to optimize your testing efforts effectively.

Regardless of whether your operations are confined to local data centers or you are grappling with escalating expenses associated with public cloud services, integrating private cloud virtualization is essential to your overall infrastructure strategy. Mirantis OpenStack for Kubernetes empowers you with the advantages of public cloud services while maintaining the dependable performance of OpenStack—all founded on the adaptable and robust structure of Kubernetes, allowing you to regain control over your cloud environment. As a premier open source infrastructure-as-a-service (IaaS) solution, OpenStack offers a comprehensive and mature setting tailored for managing virtual machines, networking, and storage. By merging virtualized infrastructure with the cloud-native ecosystem, Mirantis OpenStack for Kubernetes presents a user-friendly virtualization platform built on Kubernetes, ensuring maximum flexibility and reliability, which can significantly enhance your operational efficiency. This integration not only streamlines management but also aligns with modern DevOps practices, fostering a more agile and responsive IT environment.

Kaholo is an IT workflow automation tool for developers that uses low-code code. It allows them to automate their workflows quicker and can be used by any developer without the need for scripting or proprietary tool knowledge.

Kao Data stands at the forefront of the industry, innovating in the creation and management of data centres specifically designed for artificial intelligence and cutting-edge computing. Our platform, inspired by hyperscale models and tailored for industrial use, offers clients a secure, scalable, and environmentally friendly environment for their computing needs. Based at our Harlow campus, we support a diverse range of mission-critical high-performance computing projects, establishing ourselves as the UK's top choice for demanding, high-density, GPU-driven computing solutions. Additionally, with swift integration options available for all leading cloud providers, we enable the realization of your hybrid AI and HPC aspirations seamlessly. By prioritizing sustainability and performance, we are not just meeting current demands but also shaping the future of computing infrastructure.

MayaNAS Cloud offers a comprehensive enterprise-level software-defined storage solution that delivers exceptional performance and throughput for file storage utilizing standard object storage (S3) without requiring extra resources. This solution is entirely software-based, enabling file storage compatibility via NFS, SMB-AD, and providing robust block services through NVMeoF, iSCSI, and FC connections. Key features include a two-node high-availability setup, compression, thin provisioning, an unlimited number of policy-driven snapshots, and continuous replication capabilities. Moreover, MayaNAS is accessible as a marketplace solution across prominent public clouds like AWS, GCP, and Azure, and it can also be installed on-premises via an ISO image for bare metal setups. Additionally, the versatility of MayaNAS makes it an ideal choice for organizations looking to optimize their storage infrastructure in various environments.