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Why Demand for In-Memory Computing Platforms Keeps Growing

The demand for in-memory computing (IMC) and new IMC platforms continues to grow. What’s pushing this growth as new products like the GridGain in-memory computing platform hit the market? Download the new white paper from GridGain that explores this topic and covers what’s next for in-memory computing.

Why IMC Is Right for Today’s Fast-Data and Big-Data Applications

In-memory computing, or IMC, is being used for a variety of functions, including fintech and ecommerce to telecommunications and IoT, as it becomes well known for success with processing and analyzing big data.  Download the new report from GridGain, “Choosing the Right In-Memory Computing Solution,” to find out whether IMC is the right choice for your business. 

In-Memory Computing: Addressing Emerging Data-Intensive Use Cases

This white paper from GridGain examines the factors contributing to increased demand, the innovative directions in which the industry is heading over the next decade, and how the Apache Ignite and the GridGain in-memory computing platforms are leading the way toward the in-memory computing systems of tomorrow. Download the new report from GridGain to get a handle on what’s in store for the in-memory computing market. 

GridGain In-Memory Computing Platform Delivers Speed and Scalability

The GridGain In-Memory computing platform works to deliver speed and scalability for your large data needs. The platform is built on the Apache Ignite open source project. Download the new white paper today, “Introducing the GridGain In-Memory Computing Platform,” to find out if GridGain is the right choice for you. 

Choosing the Right In-Memory Computing Solution

This white paper reviews why in-memory computing makes sense for today’s fast-data and big-data applications. It dispels common myths about IMC and clarifies the distinctions among IMC product categories to make the process of choosing the right IMC solution for a specific use case much easier. Download the new white paper from GridGain that offers a guide to in-memory computing, and find out in-memory computing is right for your business. 

Introducing the GridGain In-Memory Computing Platform

In-memory computing is characterized by using high-performance, integrated and distributed memory systems to compute and transact on large data sets in real-time. A new white paper explores the key features of the GridGain Systems in-memory computing platform, which offers a strategic approach to in-memory computing. Download the report to learn more about this innovative platform.   

GigaSpaces Simplifies Artificial Intelligence Development with Intel BigDL

“BigDL’s efficient large-scale distributed deep learning framework, built on Apache Spark, expands the accessibility of deep learning to a broader range of big data users and data scientists,” said Michael Greene, Vice President, Software and Services Group, General Manager, System Technologies and Optimization, Intel Corporation. “The integration with GigaSpaces’ in-memory insight platform, InsightEdge, unifies fast-data analytics, artificial intelligence, and real-time applications in one simplified, affordable, and efficient analytics stack.”

Why IMC is Right for Today’s Fast-Data and Big-Data Applications

Many more companies are turning to in-memory computing (IMC) as they struggle to analyze and process increasingly large amounts of data. That said, it’s often hard to make sense of the growing world of IMC products and solutions. A recent white paper from GridGain aims to help businesses decide which solution best matches their specific needs.

Choosing the Right In-Memory Computing Solution

This white paper reviews why IMC makes sense for today’s fast-data and big-data applications, dispels common myths about IMC, and clarifies the distinctions among IMC product categories to make the process of choosing the right IMC solution for a specific use case much easier. Download now to learn more.

insideHPC Research Report on In-Memory Computing

To achieve high performance, modern computer systems rely on two basic methodologies to scale resources. A scale-up design that allows multiple cores to share a large global pool of memory and a scale-out design design that distributes data sets across the memory on separate host systems in a computing cluster. To learn more about In-Memory computing download this guide from IHPC and SGI.