Best HPC Software in Brazil

This confluence created new requirements for HPC storage because the input/output patterns for both workloads were very different. It is happening right now. Intersect360, an independent analyst firm, found that 63% of HPC users are already running machine learning programs. Hyperion Research predicts that the growth in HPC storage spending by public sector organizations and enterprises over the next three-years will be 57% faster than that for HPC compute. Seymour Cray once stated, "Anyone can make a fast CPU." The trick is to create a fast system. Anyone can build fast file storage when it comes to AI and HPC. It is possible to create a cost-effective, scalable and fast file storage system. This is possible by embedding the most popular parallel file systems in parallel storage products from HPE that are cost-effective.

High-end accelerators and processors such as Graphic Processing Units (GPU) are best for data-intensive AI, IoT, and HPC workloads that require multiple parallel processes. Businesses and research organizations have had the to make compromises when running compute-intensive workloads using cloud-based solutions. Cloud environments can be incompatible with new applications, or require high energy consumption levels. This can raise concerns about the environment. Other times, some aspects of cloud solutions are just too difficult to use. This makes it difficult to create custom cloud environments that meet business needs.

Cloud-integrated hybrid storage can be created that integrates with your existing network-attached storage and Azure Blob Storage. This appliance optimizes data access in your datacenter, in Azure or across a wide area network (WAN). Microsoft Azure FXT Edge filter is a combination of software and hardware. It provides high throughput and low latency to support hybrid storage infrastructure that supports high-performance computing (HPC). Scale-out clustering allows for non-disruptive NAS performance scale-up. To scale to millions of IOPS, and hundreds of gigabytes/s, join up to 24 FXT cluster nodes. Azure FXT Edge filter is the best choice for file-based workloads that require performance and scale. Azure FXT Edge Filer makes it easy to manage data storage. To keep your data accessible and available with minimal latency, you can transfer aging data to Azureblob Storage. Balance cloud and on-premise storage

Kombyne™, a new SaaS high performance computing (HPC), workflow tool, was initially designed for customers in the aerospace, defense, and automotive industries. It is now available to academic researchers. It allows users to subscribe for a variety of workflow solutions for HPC-related jobs, including on-the-fly extraction generation and rendering to simulation steering. Interactive monitoring and control are available with minimal simulation disruption, and no reliance upon VTK. Extract workflows and real time visualization eliminate the need for large files. In-transit workflows use a separate process that receives data from the solver and performs visualizations and analysis without interfering in the running solver. The endpoint, also known as an extract, can output point samples, cutting planes, and point samples for data science. It can also render images. The Endpoint can also be used to bridge to popular visualization codes.

The integrated system management solution for Linux®, high-performance computing (HPC), clusters is offered by HPE Performance Cluster Manager (HPCM). HPE Performance Cluster Manager offers complete provisioning, management and monitoring of clusters that scale up to Exascale-sized supercomputers. The software allows for fast system setup starting from bare metal, comprehensive hardware monitoring, management, software updates, power management and cluster health management. It makes scaling HPC clusters faster and more efficient, and integrates with a variety of third-party tools to manage and run workloads. HPE Performance Cluster Manager cuts down on the time and effort required to administer HPC systems. This results in lower total cost of ownership, increased productivity, and a higher return on investment.

Arm Allinea Studio provides a suite of tools to develop server and HPC applications for Arm-based platforms. It includes Arm-specific libraries and compilers, as well as debugging and optimization tools. Arm Performance Libraries are optimized core math libraries that can be used to run high-performance computing applications on Arm processors. These routines are available via both Fortran and C interfaces. Arm Performance Libraries are built using OpenMP across many BLAS and LAPACK, FFT and sparse procedures to maximize your performance when working in multi-processor environments.

The NVIDIA HPC Software Developer Kit (SDK), includes the proven compilers and libraries, as well as software tools that maximize developer productivity and improve the portability and performance of HPC applications. NVIDIA HPC SDK C and C++, and Fortran compilers allow GPU acceleration of HPC simulation and modeling applications using standard C++ and Fortran, OpenACC® directives and CUDA®. GPU-accelerated math libraries maximize performance for common HPC algorithms. Optimized communications libraries allow standards-based multi-GPU programming and scalable systems programming. Debugging and performance profiling tools make porting and optimizing HPC applications easier. Containerization tools allow for easy deployment on-premises and in the cloud. The HPC SDK supports NVIDIA GPUs, Arm, OpenPOWER or x86 64 CPUs running Linux.

The Nimbix Supercomputing Suite offers a range of high-performance computing (HPC), as-a-service solutions that are flexible and secure. This as-a service model for HPC, AI and Quantum in cloud gives customers access to one the largest HPC and supercomputing portfolios. It includes hardware, bare metal-as a service, and the democratization and use of advanced computing in cloud across public and privately owned data centers. HyperHub Application Marketplace is our high-performance marketplace that offers over 1,000 applications and workflows. For the best infrastructure and on-demand scalability and convenience, BullSequana HPC server can be used as bare metal. Federated supercomputing-as-a-service offers a unified service console to manage all compute zones and regions in a public or private HPC, AI, and supercomputing federation.

Kao Data is a leader in the industry. It pioneered the development and operation data centres designed for AI and advanced computing. We provide our customers a secure, scalable, and sustainable computing environment with a hyperscale platform. Kao Data is a leader in the industry for developing and operating data centres designed for AI and advanced computing. Our Harlow campus is the UK's top choice for high-density, GPU-powered computing. We can help you realize your hybrid AI and HPC goals with rapid on-ramps to all major cloud providers.

Fuzzball speeds up innovation for researchers and scientist by eliminating the burdens associated with infrastructure provisioning and administration. Fuzzball optimizes the design and execution of high-performance computing workloads. A user-friendly GUI to design, edit, and execute HPC jobs. CLI allows for comprehensive control and automation of HPC tasks. Automated data entry and exit with full compliance logs. Native integration with GPUs, on-prem storage and cloud storage. Workflow files that are portable and readable by humans. CIQ's Fuzzball modernizes HPC by using an API-first and container-optimized architectural approach. It is based on Kubernetes and provides all of the security, performance and stability found in modern infrastructure and software. Fuzzball abstracts infrastructure and automates complex workflows to drive greater efficiency and collaboration.

Amazon Elastic Compute Cloud's (Amazon EC2) instances P5 powered by NVIDIA Tensor core GPUs and P5e or P5en instances powered NVIDIA Tensor core GPUs provide the best performance in Amazon EC2 when it comes to deep learning and high-performance applications. They can help you accelerate the time to solution up to four times compared to older GPU-based EC2 instance generation, and reduce costs to train ML models up to forty percent. These instances allow you to iterate faster on your solutions and get them to market quicker. You can use P5,P5e,and P5en instances to train and deploy increasingly complex large language and diffusion models that power the most demanding generative artificial intelligent applications. These applications include speech recognition, video and image creation, code generation and question answering. These instances can be used to deploy HPC applications for pharmaceutical discovery.

Amazon EC2 UltraClusters allow you to scale up to thousands of GPUs and machine learning accelerators such as AWS trainium, providing access to supercomputing performance on demand. They enable supercomputing to be accessible for ML, generative AI and high-performance computing through a simple, pay-as you-go model, without any setup or maintenance fees. UltraClusters are made up of thousands of accelerated EC2 instance co-located within a specific AWS Availability Zone and interconnected with Elastic Fabric Adapter networking to create a petabit scale non-blocking network. This architecture provides high-performance networking, and access to Amazon FSx, a fully-managed shared storage built on a parallel high-performance file system. It allows rapid processing of large datasets at sub-millisecond latency. EC2 UltraClusters offer scale-out capabilities to reduce training times for distributed ML workloads and tightly coupled HPC workloads.

AWS High Performance Computing services (HPC) enable users to execute large-scale simulators and deep-learning workloads in the cloud. They provide virtually unlimited compute capacity and high-performance file system, as well as high-throughput network. This suite of services accelerates the innovation process by providing a wide range of cloud-based applications, including machine learning, analytics, and rapid design and testing. On-demand access to computing resources maximizes operational efficiency, allowing users the freedom to solve complex problems without the limitations of traditional infrastructure. AWS HPC includes Elastic Fabric Adapter for low-latency and high-bandwidth networks, AWS Batch to scale computing jobs, AWS ParallelCluster to simplify cluster deployment, as well as Amazon FSx, a high-performance file system. These services provide a flexible, scalable environment that is tailored to diverse HPC workloads.

Elastic Fabric Adapter is a network-interface for Amazon EC2 instances. It allows customers to run applications that require high levels of internode communication at scale. Its custom-built OS bypass hardware interface improves the performance of interinstance communications which is crucial for scaling these applications. EFA allows High-Performance Computing applications (HPC) using the Message Passing Interface, (MPI), and Machine Learning applications (ML) using NVIDIA's Collective Communications Library, (NCCL), to scale up to thousands of CPUs and GPUs. You get the performance of HPC clusters on-premises, with the elasticity and flexibility on-demand of AWS. EFA is a free networking feature available on all supported EC2 instances. Plus, EFA works with the most common interfaces, libraries, and APIs for inter-node communication.

AWS ParallelCluster, an open-source tool for cluster management, simplifies the deployment of High-Performance Computing clusters (HPC) on AWS. It automates resource setup, including compute nodes and a shared filesystem. It also supports multiple instance types and queues for job submission. ParallelCluster can be accessed via a graphical interface, command line interface, or API. This allows for flexible cluster management and configuration. The tool integrates with AWS Batch and Slurm to facilitate seamless migration of HPC workloads into the cloud. AWS ParallelCluster comes at no extra cost; users pay only for the AWS resources used by their applications. AWS ParallelCluster allows you to use a simple text document to model, provision and dynamically scale resources for your applications. This can be done in an automated, secure and automated manner.

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).

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.