The volume, variety, and velocity properties of big data and the valuable information it contains have motivated the investigation of many new parallel data processing systems in addition to the ...

Big data frameworks prioritise performance by leveraging parallel processing as well. Apache Spark, a popular big data framework, uses in-memory processing to boost the speed of data processing ...

The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized ...

Modern computing has many foundational building blocks, including central processing units (CPUs), graphics processing units (GPUs) and data processing units (DPUs).. However, what almost all modern ...

Hadoop MapReduce, a YARN-based system for parallel processing of large data sets. Apache Spark. ... Spark has become one of the key big data distributed processing frameworks, ...

If your company needs high-performance computing for its big data, an in-house operation might work best. Here's what you need to know, including how high-performance computing and Hadoop differ.

NASHUA, N.H., Feb. 8, 2018 /CNW/ -- Parallel Wireless, Inc., the leader in end-to-end 2G, 3G, and 4G Open RAN solutions announced today a collaboration on Big Data virtualized Analytics ...

At MIT's Emerging Tech Conference, Intel, Cisco and HP contend that parallel processing will be the big driver for the data center.

The volume, variety, and velocity properties of big data and the valuable information it contains have motivated the investigation of many new parallel data processing systems in addition to the ...

Abstract: The volume, variety, and velocity properties of big data and the valuable information it contains have motivated the investigation of many new parallel data processing systems in addition to ...