לקוח: Dell
פורמט: נייר עמדה
גודל: 849 קילו-בייט
שפה: אנגלית
תאריך: 20.01.2021

The Total Economic Impact™ Of Dell EMC Ready Solutions For HPC

High-performance computing (HPC) is the convergence of clusters of computational nodes, high volumes of storage, and bandwidth that results
in the fastest possible computing for complex problem solving. HPC demand is steadily growing as enterprises increasingly rely on sophisticated data analysis, modeling, and simulation to find answers to big questions and to make big decisions. While most existing use cases have been centered around solving for mathematical models and simulation of complex systems, there has been rapid growth in demand for artificial intelligence (AI) use cases.

Dell EMC Ready Solutions for HPC enables organizations to accelerate their science, engineering, analytics, and AI initiatives with a diverse
portfolio of products and services curated for individual HPC workload requirements. The portfolio contains a wide selection of price and
performance optimized hardware, management and orchestration software, and domain-specific services. Dell Technologies and Intel commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Dell EMC Ready Solutions for HPC. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Ready Solutions for HPC on their organizations.

To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed several customers with years of
experience using Ready Solutions for HPC. These organizations used Dell’s HPC solutions to conduct scientific research, advance AI studies,
process seismographic data, and assess financial risk on a global scale. Prior to using Dell EMC Ready Solutions for HPC, the customers used a
mixture of homegrown and legacy HPC systems. These alternatives proved difficult to maintain and did not meet the firms’ growing compute
demands.

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Date: 1.8.2018

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