Cognitive computing, which aims to simulate human thought and reasoning, could be considered the ultimate goal of information technology and is set to begin a new era in 2017, according to Kinetica's Eric Mizell, vice president, global solutions engineering.

There are four major trends that are driving the adoption of GPU-accelerated databases in this new 2017 Cognitive Computing era, according to Mizell. These include:

Trend #1: GPUs will revolutionize real-time intelligence in 2017

Graphical Processing Units (GPUs) deliver up to 100-times better performance compared to leading in-memory and analytical databases. This is due to the GPU's parallelized processing architecture that contains over 4,000 cores, compared to 16-32 cores in today's typical multi-core CPUs. The GPU's small cores are able to efficiently perform similar instructions in parallel. This ability makes them ideally suited for these new compute-intensive workloads that are essential for real-time analysis of large streaming data sets.

Trend #2: GPUs will transform the Cloud into a turbo- charged network

Amazon already offers GPU-powered instances within its cloud service, and Microsoft and Google are not far behind, as they have both announced plans to offer GPU instances in their cloud offerings. All of these cloud service providers are turning to GPUs in order to gain a competitive advantage and offer their customers dramatic performance improvements. Microsoft and Google are both expected to begin offering GPU instances in 2017.

Trend #3: GPU-accelerated databases will soon have enterprise-class capabilities

Major enhancements in both security and high availability in GPUs will occur in 2017, and these features will build on the GPU's proven enterprise-class performance and scalability abilities. In terms of security, role-and group-based authorization as well as user authentication support will make GPU-accelerated databases a good choice for applications that need to comply with security regulations, including personal privacy protections. Data replication with...

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