High-Performance Computing Systems
A Solution for Data-Intensive Applications
High-performance computing systems play a critical role in accelerating data processing and enabling advanced applications across industries. Organizations require scalable, high-performance solutions to manage increasingly complex workloads, from artificial intelligence (AI) and machine learning (ML) to scientific research and enterprise IT.
SC//HyperCore™ Hypervisor deliver a robust, efficient, and scalable infrastructure designed to meet the growing demand for high-performance computing solutions. Whether processing large datasets, running simulations, or handling high-performance data analytics, Scale Computing™ provides the foundation to optimize operations, enhance resilience, and achieve performance goals—while simplifying IT management and reducing costs.
An Optimized High-Performance Solution
Deliver maximum performance for high-performance workloads. With advanced features such as pooled block storage, intelligent data placement, and automated workload balancing, your computational tasks are executed efficiently, minimizing latency and maximizing throughput.
Easily scale your environment as your computational needs grow. SC//HyperCore software supports seamless expansion without disruption, allowing you to add resources on-demand, ensuring your infrastructure can adapt to ever-evolving workloads.
Managing high-performance infrastructure can be complex, but SC//HyperCore virtualization simplifies the process with its intuitive management interface and automation capabilities. From deployment to ongoing maintenance, the platform streamlines operations, freeing your IT team to focus on innovation rather than infrastructure.
How High-Performance Computing Powers Advanced Applications
Enhanced Performance for High-Performance Applications
Enterprise infrastructure has become volatile for data-intensive industries, whether you are delivering critical patient outcomes, customized and real-time customer experiences, or advancing supply chains for zero-touch delivery and logistics. Scale Computing with Nvidia GPU technologies offers IT teams the ability to deliver high-performance virtual desktop infrastructure and streamlined application experiences for employees and customers across industries.
- Scientific Research
- Graphical Design
- Engineering
- Architecture
- Manufacturing
- Finance
- Education
- Government
Empowering Knowledge Workers with High-Performance Solutions
Today's knowledge workers need modern, high-end productivity applications that require AI-enhanced graphics, video, and image processing to speed up creative workflows that are being collaboratively worked on globally or remotely from the traditional in-person workplace. With the added performance of Nvidia T4’s GPU accelerators, SC//HyperCore virtualization suite delivers a highly-available and cost-effective virtual desktop solution to help transition your workforce into the new work-from-anywhere landscape of doing business.
- AutoCAD
- Solidworks
- Revit
- Civil 3D
- Photoshop
- Resolve
- Premiere
- ArcGIS
- Cinema 4D
High-Performance for Virtual Desktop Infrastructure (VDI)
Scale Computing's advanced architecture is designed to deliver outstanding performance for Virtual Desktop Infrastructure (VDI). By ensuring fast, reliable, and scalable virtual desktop environments, empowering organizations to meet the needs of modern workforces with ease and efficiency. Offloading demanding workloads to GPU cores minimizes latency and ensures a smooth and responsive desktop experience, even under heavy user demands.
Dynamically scale resources to align with workload demands further optimizes VDI environments, providing consistent performance while adapting to evolving needs. The platform’s intelligent workload balancing and automation ensure efficient resource utilization, reducing management overhead and delivering cost-effective scalability.
By combining GPU acceleration, scalability, and intelligent resource management, providing a powerful foundation for VDI, enabling organizations to support their users with unparalleled performance and reliability.
Optimized for Parallel Workloads
GPU-enabled hardware significantly advances its ability to handle workloads that require parallel processing, which is fundamental to high-performance computing. Parallel processing allows multiple calculations or processes to be executed simultaneously, significantly enhancing the speed and efficiency of computational tasks.
These GPU cores can be leveraged to process vast amounts of data simultaneously, particularly beneficial for workloads like scientific simulations, financial modeling, machine learning (ML), and artificial intelligence (AI).
For example, GPUs play a critical role in processing large neural network models to deliver real-time predictions in AI inferencing. Consider an AI-powered retail application that leverages customer data to make personalized product recommendations.
With GPU-enabled nodes, inference tasks - such as analyzing purchase history, browsing behavior, and demographic data - are executed in milliseconds, enabling dynamic, real-time recommendations that enhance customer experience and drive sales.
Accelerated AI & Data Processing
One of the significant advantages, especially in GPU-equipped configurations, is its capability for real-time processing and analysis, which is critical for computer vision applications. These applications rely on rapid, accurate processing of visual data to enable tasks such as object detection, image classification, facial recognition, and automated quality inspection. Additional support for a range of vision-intensive workloads makes it suitable for diverse industries, from retail and healthcare to manufacturing.
Dramatically speed up the processing of large image datasets and video streams by distributing the computational load across GPU cores.
This parallel processing capability enables faster analysis times, allowing data scientists, engineers, and developers to train and deploy vision models more efficiently while supporting real-time inference for mission-critical applications.
SC//HyperCore virtualization suite can be scaled to meet the specific computer vision needs of different industries and applications, from small startups developing cutting-edge AI applications to large enterprises deploying vision systems at scale. This scalability ensures that organizations can adjust their computational resources based on the complexity and volume of their vision-related tasks, delivering unmatched performance and flexibility.
Scalable, Hybrid High-Performance Solutions
Scale Computing delivers scalable, hybrid high-performance solutions that combine the power of on-premises infrastructure with the flexibility of cloud resources. By leveraging intelligent automation, high-performance storage, and GPU acceleration, ensuring seamless workload balancing and optimized resource utilization for demanding applications like AI-driven analytics, computer vision, and real-time data processing.
With built-in high availability and simplified management, organizations can scale their high-performance environments effortlessly, whether at the edge, in the data center, or across hybrid deployments.
"Our RPO and RTO dramatically reduced from three days to a matter of minutes. We can now use this time to focus on other IT priorities making a real difference to the business. With Scale Computing we can align IT strategy with business growth."
IT Manager at Penlon
Real-World Impact of High-Performance Computing
Scale computing clusters dramatically reduced management time, allowing the IT department to focus on other challenges rather than IT infrastructure. In addition, the high-performance technology offered scale-out architecture, providing Penlon with room to expand.
Scale Computing for Accelerated VDI and High-Performance Applications
Frequently Asked Questions
What is high-performance computing used for?
High-performance computing (HPC) is used for data-intensive applications such as AI training, financial modeling, climate simulations, and real-time analytics, including computer vision for retail surveillance, fraud detection, and personalized recommendations.
How does HPC differ from traditional computing?
HPC utilizes parallel processing, high-speed interconnects, and specialized hardware (such as GPUs) to perform large-scale computations much faster than traditional computing, which relies on sequential processing.
What industries benefit from HPC?
Industries such as retail, healthcare, finance, manufacturing, energy, and scientific research rely on HPC for tasks like fraud detection, customer behavior prediction, drug discovery, risk analysis, weather forecasting, and engineering simulations.
What are the key components of an HPC system?
An HPC system typically includes high-performance processors (CPUs and GPUs), fast interconnects (InfiniBand, NVLink), scalable memory, parallel storage (NVMe SSDs, Lustre file systems), and workload management software for efficient resource allocation.
What are examples of high-performance computing?
Examples of HPC include supercomputers like Summit and Fugaku, AI training clusters, financial risk modeling platforms, climate simulations, and real-time genomics analysis for precision medicine.
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