Alternatives to Warewulf

Amazon Elastic Container Service (ECS) is a comprehensive container orchestration platform that is fully managed. Notable clients like Duolingo, Samsung, GE, and Cook Pad rely on ECS to operate their critical applications due to its robust security, dependability, and ability to scale. There are multiple advantages to utilizing ECS for container management. For one, users can deploy their ECS clusters using AWS Fargate, which provides serverless computing specifically designed for containerized applications. By leveraging Fargate, customers eliminate the need for server provisioning and management, allowing them to allocate costs based on their application's resource needs while enhancing security through inherent application isolation. Additionally, ECS plays a vital role in Amazon’s own infrastructure, powering essential services such as Amazon SageMaker, AWS Batch, Amazon Lex, and the recommendation system for Amazon.com, which demonstrates ECS’s extensive testing and reliability in terms of security and availability. This makes ECS not only a practical option but a proven choice for organizations looking to optimize their container operations efficiently.

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.

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).

Kubernetes serves as a powerful foundation for transformative ideas. It enables developers to innovate and deliver projects more rapidly through the premier hybrid cloud and enterprise container solution. Red Hat OpenShift simplifies the process with automated installations, updates, and comprehensive lifecycle management across the entire container ecosystem, encompassing the operating system, Kubernetes, cluster services, and applications on any cloud platform. This service allows teams to operate with speed, flexibility, assurance, and a variety of options. You can code in production mode wherever you prefer to create, enabling a return to meaningful work. Emphasizing security at all stages of the container framework and application lifecycle, Red Hat OpenShift provides robust, long-term enterprise support from a leading contributor to Kubernetes and open-source technology. It is capable of handling the most demanding workloads, including AI/ML, Java, data analytics, databases, and more. Furthermore, it streamlines deployment and lifecycle management through a wide array of technology partners, ensuring that your operational needs are met seamlessly. This integration of capabilities fosters an environment where innovation can thrive without compromise.

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.

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.

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.

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.

NVIDIA Base Command Manager provides rapid deployment and comprehensive management for diverse AI and high-performance computing clusters, whether at the edge, within data centers, or across multi- and hybrid-cloud settings. This platform automates the setup and management of clusters, accommodating sizes from a few nodes to potentially hundreds of thousands, and is compatible with NVIDIA GPU-accelerated systems as well as other architectures. It facilitates orchestration through Kubernetes, enhancing the efficiency of workload management and resource distribution. With additional tools for monitoring infrastructure and managing workloads, Base Command Manager is tailored for environments that require accelerated computing, making it ideal for a variety of HPC and AI applications. Available alongside NVIDIA DGX systems and within the NVIDIA AI Enterprise software suite, this solution enables the swift construction and administration of high-performance Linux clusters, thereby supporting a range of applications including machine learning and analytics. Through its robust features, Base Command Manager stands out as a key asset for organizations aiming to optimize their computational resources effectively.

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.

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.

xCAT, or Extreme Cloud Administration Toolkit, is a versatile open-source solution aimed at streamlining the deployment, scaling, and oversight of both bare metal servers and virtual machines. It delivers extensive management functionalities tailored for environments such as high-performance computing clusters, render farms, grids, web farms, online gaming infrastructures, cloud setups, and data centers. Built on a foundation of established system administration practices, xCAT offers a flexible framework that allows system administrators to identify hardware servers, perform remote management tasks, deploy operating systems on physical or virtual machines in both disk and diskless configurations, set up and manage user applications, and execute parallel system management operations. This toolkit is compatible with a range of operating systems, including Red Hat, Ubuntu, SUSE, and CentOS, as well as architectures such as ppc64le, x86_64, and ppc64. Moreover, it supports various management protocols, including IPMI, HMC, FSP, and OpenBMC, which enable seamless remote console access. In addition to its core functionalities, xCAT's extensible nature allows for ongoing enhancements and adaptations to meet the evolving needs of modern IT infrastructures.

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.

ClusterVisor serves as an advanced system for managing HPC clusters, equipping users with a full suite of tools designed for deployment, provisioning, oversight, and maintenance throughout the cluster's entire life cycle. The system boasts versatile installation methods, including an appliance-based deployment that separates cluster management from the head node, thereby improving overall system reliability. Featuring LogVisor AI, it incorporates a smart log file analysis mechanism that leverages artificial intelligence to categorize logs based on their severity, which is essential for generating actionable alerts. Additionally, ClusterVisor streamlines node configuration and management through a collection of specialized tools, supports the management of user and group accounts, and includes customizable dashboards that visualize information across the cluster and facilitate comparisons between various nodes or devices. Furthermore, the platform ensures disaster recovery by maintaining system images for the reinstallation of nodes, offers an easy-to-use web-based tool for rack diagramming, and provides extensive statistics and monitoring capabilities, making it an invaluable asset for HPC cluster administrators. Overall, ClusterVisor stands as a comprehensive solution for those tasked with overseeing high-performance computing environments.

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.

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.

Appvia Wayfinder provides a dynamic solution to manage your cloud infrastructure. It gives your developers self-service capabilities that let them manage and provision cloud resources without any hitch. Wayfinder's core is its security-first strategy, which is built on principles of least privilege and isolation. You can rest assured that your resources are safe. Platform teams rejoice! Centralised control allows you to guide your team and maintain organisational standards. But it's not just business. Wayfinder provides a single pane for visibility. It gives you a bird's-eye view of your clusters, applications, and resources across all three clouds. Join the leading engineering groups worldwide who rely on Appvia Wayfinder for cloud deployments. Do not let your competitors leave behind you. Watch your team's efficiency and productivity soar when you embrace Wayfinder!

Introducing K8 Studio, the premier cross-platform client IDE designed for streamlined management of Kubernetes clusters. Effortlessly deploy your applications across leading platforms like EKS, GKE, AKS, or even on your own bare metal infrastructure. Enjoy the convenience of connecting to your cluster through a user-friendly interface that offers a clear visual overview of nodes, pods, services, and other essential components. Instantly access logs, receive in-depth descriptions of elements, and utilize a bash terminal with just a click. K8 Studio enhances your Kubernetes workflow with its intuitive features. With a grid view for a detailed tabular representation of Kubernetes objects, users can easily navigate through various components. The sidebar allows for the quick selection of object types, ensuring a fully interactive experience that updates in real time. Users benefit from the ability to search and filter objects by namespace, as well as rearranging columns for customized viewing. Workloads, services, ingresses, and volumes are organized by both namespace and instance, facilitating efficient management. Additionally, K8 Studio enables users to visualize the connections between objects, allowing for a quick assessment of pod counts and current statuses. Dive into a more organized and efficient Kubernetes management experience with K8 Studio, where every feature is designed to optimize your workflow.

Welcome to the OpenHPC website, a platform born from a collaborative community effort aimed at unifying various essential components necessary for the deployment and management of High Performance Computing (HPC) Linux clusters. This initiative encompasses tools for provisioning, resource management, I/O clients, development utilities, and a range of scientific libraries, all designed with HPC integration as a priority. The packages offered by OpenHPC are specifically pre-built to serve as reusable building blocks for the HPC community, ensuring efficiency and accessibility. As the community evolves, there are plans to define and create abstraction interfaces among key components to further improve modularity and interchangeability within the ecosystem. Representing a diverse array of stakeholders including software vendors, equipment manufacturers, research institutions, and supercomputing facilities, this community is dedicated to the seamless integration of widely used components that are available for open-source distribution. By working together, they aim to foster innovation and collaboration in the field of High Performance Computing. This collective effort not only enhances existing technologies but also paves the way for future advancements in the HPC landscape.

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.

OpenSVC is an innovative open-source software solution aimed at boosting IT productivity through a comprehensive suite of tools that facilitate service mobility, clustering, container orchestration, configuration management, and thorough infrastructure auditing. The platform is divided into two primary components: the agent and the collector. Acting as a supervisor, clusterware, container orchestrator, and configuration manager, the agent simplifies the deployment, management, and scaling of services across a variety of environments, including on-premises systems, virtual machines, and cloud instances. It is compatible with multiple operating systems, including Unix, Linux, BSD, macOS, and Windows, and provides an array of features such as cluster DNS, backend networks, ingress gateways, and scalers to enhance functionality. Meanwhile, the collector plays a crucial role by aggregating data reported by agents and retrieving information from the site’s infrastructure, which encompasses networks, SANs, storage arrays, backup servers, and asset managers. This collector acts as a dependable, adaptable, and secure repository for data, ensuring that IT teams have access to vital information for decision-making and operational efficiency. Together, these components empower organizations to streamline their IT processes and maximize resource utilization effectively.

Spectro Cloud’s Palette platform provides enterprises with a powerful and scalable solution for managing Kubernetes clusters across multiple environments, including cloud, edge, and on-premises data centers. By leveraging full-stack declarative orchestration, Palette allows teams to define cluster profiles that ensure consistency while preserving the freedom to customize infrastructure, container workloads, OS, and Kubernetes distributions. The platform’s lifecycle management capabilities streamline cluster provisioning, upgrades, and maintenance across hybrid and multi-cloud setups. It also integrates with a wide range of tools and services, including major cloud providers like AWS, Azure, and Google Cloud, as well as Kubernetes distributions such as EKS, OpenShift, and Rancher. Security is a priority, with Palette offering enterprise-grade compliance certifications such as FIPS and FedRAMP, making it suitable for government and regulated industries. Additionally, the platform supports advanced use cases like AI workloads at the edge, virtual clusters, and multitenancy for ISVs. Deployment options are flexible, covering self-hosted, SaaS, or airgapped environments to suit diverse operational needs. This makes Palette a versatile platform for organizations aiming to reduce complexity and increase operational control over Kubernetes.

Red Hat Advanced Cluster Management for Kubernetes allows users to oversee clusters and applications through a centralized interface, complete with integrated security policies. By enhancing the capabilities of Red Hat OpenShift, it facilitates the deployment of applications, the management of multiple clusters, and the implementation of policies across numerous clusters at scale. This solution guarantees compliance, tracks usage, and maintains uniformity across deployments. Included with Red Hat OpenShift Platform Plus, it provides an extensive array of powerful tools designed to secure, protect, and manage applications effectively. Users can operate from any environment where Red Hat OpenShift is available and can manage any Kubernetes cluster within their ecosystem. The self-service provisioning feature accelerates application development pipelines, enabling swift deployment of both legacy and cloud-native applications across various distributed clusters. Additionally, self-service cluster deployment empowers IT departments by automating the application delivery process, allowing them to focus on higher-level strategic initiatives. As a result, organizations can achieve greater efficiency and agility in their IT operations.

Apache Helix serves as a versatile framework for managing clusters, ensuring the automatic oversight of partitioned, replicated, and distributed resources across a network of nodes. This tool simplifies the process of reallocating resources during instances of node failure, system recovery, cluster growth, and configuration changes. To fully appreciate Helix, it is essential to grasp the principles of cluster management. Distributed systems typically operate on multiple nodes to achieve scalability, enhance fault tolerance, and enable effective load balancing. Each node typically carries out key functions within the cluster, such as data storage and retrieval, as well as the generation and consumption of data streams. Once set up for a particular system, Helix functions as the central decision-making authority for that environment. Its design ensures that critical decisions are made with a holistic view, rather than in isolation. Although integrating these management functions directly into the distributed system is feasible, doing so adds unnecessary complexity to the overall codebase, which can hinder maintainability and efficiency. Therefore, utilizing Helix can lead to a more streamlined and manageable system architecture.

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.

Dataproc enhances the speed, simplicity, and security of open source data and analytics processing in the cloud. You can swiftly create tailored OSS clusters on custom machines to meet specific needs. Whether your project requires additional memory for Presto or GPUs for machine learning in Apache Spark, Dataproc facilitates the rapid deployment of specialized clusters in just 90 seconds. The platform offers straightforward and cost-effective cluster management options. Features such as autoscaling, automatic deletion of idle clusters, and per-second billing contribute to minimizing the overall ownership costs of OSS, allowing you to allocate your time and resources more effectively. Built-in security measures, including default encryption, guarantee that all data remains protected. With the JobsAPI and Component Gateway, you can easily manage permissions for Cloud IAM clusters without the need to configure networking or gateway nodes, ensuring a streamlined experience. Moreover, the platform's user-friendly interface simplifies the management process, making it accessible for users at all experience levels.

The latest iterations of Docker feature swarm mode, which allows for the native management of a cluster known as a swarm, composed of multiple Docker Engines. Using the Docker CLI, one can easily create a swarm, deploy various application services within it, and oversee the swarm's operational behaviors. The Docker Engine integrates cluster management seamlessly, enabling users to establish a swarm of Docker Engines for service deployment without needing any external orchestration tools. With a decentralized architecture, the Docker Engine efficiently manages node role differentiation at runtime rather than at deployment, allowing for the simultaneous deployment of both manager and worker nodes from a single disk image. Furthermore, the Docker Engine adopts a declarative service model, empowering users to specify the desired state of their application's service stack comprehensively. This streamlined approach not only simplifies the deployment process but also enhances the overall efficiency of managing complex applications.

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.

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.

Amazon EKS Anywhere is a recently introduced option for deploying Amazon EKS that simplifies the process of creating and managing Kubernetes clusters on-premises, whether on your dedicated virtual machines (VMs) or bare metal servers. This solution offers a comprehensive software package designed for the establishment and operation of Kubernetes clusters in local environments, accompanied by automation tools for effective cluster lifecycle management. EKS Anywhere ensures a uniform management experience across your data center, leveraging the capabilities of Amazon EKS Distro, which is the same Kubernetes version utilized by EKS on AWS. By using EKS Anywhere, you can avoid the intricacies involved in procuring or developing your own management tools to set up EKS Distro clusters, configure the necessary operating environment, perform software updates, and manage backup and recovery processes. It facilitates automated cluster management, helps cut down support expenses, and removes the need for multiple open-source or third-party tools for running Kubernetes clusters. Furthermore, EKS Anywhere comes with complete support from AWS, ensuring that users have access to reliable assistance whenever needed. This makes it an excellent choice for organizations looking to streamline their Kubernetes operations while maintaining control over their infrastructure.

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.

IBM Spectrum LSF Suites serves as a comprehensive platform for managing workloads and scheduling jobs within distributed high-performance computing (HPC) environments. Users can leverage Terraform-based automation for the seamless provisioning and configuration of resources tailored to IBM Spectrum LSF clusters on IBM Cloud. This integrated solution enhances overall user productivity and optimizes hardware utilization while effectively lowering system management expenses, making it ideal for mission-critical HPC settings. Featuring a heterogeneous and highly scalable architecture, it accommodates both traditional high-performance computing tasks and high-throughput workloads. Furthermore, it is well-suited for big data applications, cognitive processing, GPU-based machine learning, and containerized workloads. With its dynamic HPC cloud capabilities, IBM Spectrum LSF Suites allows organizations to strategically allocate cloud resources according to workload demands, supporting all leading cloud service providers. By implementing advanced workload management strategies, including policy-driven scheduling that features GPU management and dynamic hybrid cloud capabilities, businesses can expand their capacity as needed. This flexibility ensures that companies can adapt to changing computational requirements while maintaining efficiency.

Efficiently manage multicluster environments for Azure Kubernetes Service (AKS) that involve tasks such as workload distribution, north-south traffic load balancing for incoming requests to various clusters, and coordinated upgrades across different clusters. The fleet cluster offers a centralized management system for overseeing all your clusters on a large scale. A dedicated hub cluster manages the upgrades and the configuration of your Kubernetes clusters seamlessly. Through Kubernetes configuration propagation, you can apply policies and overrides to distribute resources across the fleet's member clusters effectively. The north-south load balancer regulates the movement of traffic among workloads situated in multiple member clusters within the fleet. You can group various Azure Kubernetes Service (AKS) clusters to streamline workflows involving Kubernetes configuration propagation and networking across multiple clusters. Furthermore, the fleet system necessitates a hub Kubernetes cluster to maintain configurations related to placement policies and multicluster networking, thereby enhancing operational efficiency and simplifying management tasks. This approach not only optimizes resource usage but also helps in maintaining consistency and reliability across all clusters involved.

DxEnterprise is a versatile Smart Availability software that operates across multiple platforms, leveraging its patented technology to support Windows Server, Linux, and Docker environments. This software effectively manages various workloads at the instance level and extends its capabilities to Docker containers as well. DxEnterprise (DxE) is specifically tuned for handling native or containerized Microsoft SQL Server deployments across all platforms, making it a valuable tool for database administrators. Additionally, it excels in managing Oracle databases on Windows systems. Beyond its compatibility with Windows file shares and services, DxE offers support for a wide range of Docker containers on both Windows and Linux, including popular relational database management systems such as Oracle, MySQL, PostgreSQL, MariaDB, and MongoDB. Furthermore, it accommodates cloud-native SQL Server availability groups (AGs) within containers, ensuring compatibility with Kubernetes clusters and diverse infrastructure setups. DxE's seamless integration with Azure shared disks enhances high availability for clustered SQL Server instances in cloud environments, making it an ideal solution for businesses seeking reliability in their database operations. Its robust features position it as an essential asset for organizations aiming to maintain uninterrupted service and optimal performance.

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.

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.

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.

You have the ability to deploy clusters as needed and automatically manage their scaling, allowing you to concentrate solely on processing, analyzing, and reporting big data. Leveraging years of experience in massively distributed computing, our operations team expertly handles the intricacies of cluster management. During peak demand, clusters can be automatically expanded to enhance computing power, while they can be contracted during quieter periods to minimize costs. A user-friendly management console is available to simplify tasks such as cluster oversight, template customization, task submissions, and monitoring of alerts. By integrating with the BCC, it enables businesses to focus on their core operations during busy times while assisting the BMR in processing big data during idle periods, ultimately leading to reduced overall IT costs. This seamless integration not only streamlines operations but also enhances efficiency across the board.

SUSE Rancher Prime meets the requirements of DevOps teams involved in Kubernetes application deployment as well as IT operations responsible for critical enterprise services. It is compatible with any CNCF-certified Kubernetes distribution, while also providing RKE for on-premises workloads. In addition, it supports various public cloud offerings such as EKS, AKS, and GKE, and offers K3s for edge computing scenarios. The platform ensures straightforward and consistent cluster management, encompassing tasks like provisioning, version oversight, visibility and diagnostics, as well as monitoring and alerting, all backed by centralized audit capabilities. Through SUSE Rancher Prime, automation of processes is achieved, and uniform user access and security policies are enforced across all clusters, regardless of their deployment environment. Furthermore, it features an extensive catalog of services designed for the development, deployment, and scaling of containerized applications, including tools for app packaging, CI/CD, logging, monitoring, and implementing service mesh solutions, thereby streamlining the entire application lifecycle. This comprehensive approach not only enhances operational efficiency but also simplifies the management of complex environments.

Fuzzball propels innovation among researchers and scientists by removing the complexities associated with infrastructure setup and management. It enhances the design and execution of high-performance computing (HPC) workloads, making the process more efficient. Featuring an intuitive graphical user interface, users can easily design, modify, and run HPC jobs. Additionally, it offers extensive control and automation of all HPC operations through a command-line interface. With automated data handling and comprehensive compliance logs, users can ensure secure data management. Fuzzball seamlessly integrates with GPUs and offers storage solutions both on-premises and in the cloud. Its human-readable, portable workflow files can be executed across various environments. CIQ’s Fuzzball redefines traditional HPC by implementing an API-first, container-optimized architecture. Operating on Kubernetes, it guarantees the security, performance, stability, and convenience that modern software and infrastructure demand. Furthermore, Fuzzball not only abstracts the underlying infrastructure but also automates the orchestration of intricate workflows, fostering improved efficiency and collaboration among teams. This innovative approach ultimately transforms how researchers and scientists tackle computational challenges.

Slurm Workload Manager, which was previously referred to as Simple Linux Utility for Resource Management (SLURM), is an open-source and cost-free job scheduling and cluster management system tailored for Linux and Unix-like operating systems. Its primary function is to oversee computing tasks within high-performance computing (HPC) clusters and high-throughput computing (HTC) settings, making it a popular choice among numerous supercomputers and computing clusters globally. As technology continues to evolve, Slurm remains a critical tool for researchers and organizations requiring efficient resource management.

Evidian SafeKit is a robust software solution aimed at achieving high availability for crucial applications across both Windows and Linux systems. This comprehensive tool combines several features, including load balancing, real-time synchronous file replication, automatic failover for applications, and seamless failback after server outages, all packaged within one product. By doing so, it removes the requirement for additional hardware like network load balancers or shared disks, and it also eliminates the need for costly enterprise versions of operating systems and databases. SafeKit's innovative software clustering allows users to establish mirror clusters that ensure real-time data replication and failover, as well as farm clusters that facilitate both load balancing and failover capabilities. Furthermore, it supports advanced configurations like farm plus mirror clusters and active-active clusters, enhancing flexibility and performance. Its unique shared-nothing architecture greatly simplifies the deployment process, making it particularly advantageous for use in remote locations by circumventing the challenges typically associated with shared disk clusters. In summary, SafeKit provides an effective and streamlined solution for maintaining application availability and data integrity across diverse environments.

Displaying only an RTF-Editor in a pop-up does not align with our vision of WYSIWYG; authors require precise control over aspects such as paragraph lengths, line breaks, table dimensions, and image sizes to produce visually appealing content. The system should utilize tags and server-side JavaScript, devoid of any Java within template code. OpenWGA Developer Studio enhances the software development journey by providing all essential tools for the creation, development, deployment, and sharing of OpenWGA web applications. With a suite of advanced technologies—including secure cluster architecture, JMX monitoring, SSO via SPNEGO, CMIS, and an integrated REST-API—OpenWGA Java CMS stands out as the ideal platform for executing business-critical enterprise applications. Additionally, the OpenWGA CMS cluster management framework facilitates not only secure inter-cluster communication and distributed task execution but also incorporates its own session replication system, optimizing resource management for better performance. This comprehensive approach ensures that developers can focus on delivering high-quality applications without the overhead of managing complex backend processes.

In summary, OKD represents a highly opinionated version of Kubernetes. At its core, Kubernetes consists of various software and architectural patterns designed to manage applications on a large scale. While we incorporate some features directly into Kubernetes through modifications, the majority of our enhancements come from "preinstalling" a wide array of software components known as Operators into the deployed cluster. These Operators manage the over 100 essential elements of our platform, including OS upgrades, web consoles, monitoring tools, and image-building functionalities. OKD is versatile and suitable for deployment across various environments, from cloud infrastructures to on-premise hardware and edge computing scenarios. The installation process is automated for certain platforms, like AWS, while also allowing for customization in other environments, such as bare metal or lab settings. OKD embraces best practices in development and technology, making it an excellent platform for technologists and students alike to explore, innovate, and engage with the broader cloud ecosystem. Furthermore, as an open-source project, it encourages community contributions and collaboration, fostering a rich environment for learning and growth.

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.