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Tag: Parallel processing

Big Data Investment Pays Off for PerkinElmer

Nearly a decade ago, the folks at PerkinElmer made the decision to rebuild their flagship software offering for managing scientific research. As data was growing and becoming more diverse, the Oracle-based relational tec Read more…

Neo4j Going Distributed with Graph Database

Neo4j is the leader in the burgeoning graph database market, with 17 years in development and thousands of open source users. But the database has a hard limit in terms of scalability, since it essentially was restricted Read more…

Why Every Python Developer Will Love Ray

There are many reasons why Python has emerged as the number one language for data science. It's easy to get started and relatively forgiving for beginners, yet it's also powerful and extensible enough for experts to take Read more…

Is GOLAP the Next Wave for Big Data Warehousing?

The 1990s and 2000s saw the rise of the relational databases for transaction processing (OLTP) as well as analytical processing (OLAP). As the volume and variety of data explodes in the 2010s, database experts are lookin Read more…

Anaconda Enterprise Now Supports GPU Clusters

Organizations that need to train machine learning models on massive amounts of data may be interested in the latest release of Anaconda Enterprise, which adds support for training on GPU clusters. Customers running An Read more…

New Approach Seeks to Automate Parallel Programming

Artificial intelligence researchers are leveraging an emerging divide-and-conquer computing approach called "dynamic programming" to greatly accelerate the process of solving problems ranging from genomic analysis to cyb Read more…

Distributed Computing Tops List of Hottest Job Skills

If you have cloud and distributed computing skills, your job prospects for 2016 are golden. That's because those particular job skills—which parallel the rise of Hadoop and other distributed computing frameworks--topp Read more…

HP Diving Deeper into R Parallelization

Despite R’s popularity as a statistical tool, its single-threaded nature might be a short-coming in scaling its use as a tool for big data applications. Not if they can help it, says HP. Read more…

Proteomic Research Unfurls Cancer Conundrum

Oncologist David Agus teamed up with Danny Hillis, who counts entrepreneur, former VP of Disney, and pioneer of parallel processing among his descriptors. The two formed Applied Proteomics, a company designed to help map proteins within the human body and determine their interactions with cancerous cells and vice versa. Read more…

Pushing Parallel Barriers Skyward

Some researchers believe that parallel processing will not be enough to meet the huge data requirements of future massive-scale astronomical surveys. Specifically, several researchers from the Korea Institute of Science and Technology Information including... Read more…

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