H2O is an open source predictive analytics platform for data scientists
and business analysts who need scalable and fast machine learning. Unlike
traditional analytics tools, H2O provides a combination of extraordinary
math and high performance parallel processing with unrivaled ease of use.
H2O speaks the language of data science with support for R, Python, Scala,
Java and a robust REST API. Smart business applications are powered by
H2O’s nano-fast scoring engine.
High processing efficiency demands greater hardware capabilities and the conventional ways of increasing speed was to employ distributed computing on multi-core CPUs with faster clock rates. The exponential increase in data available for processing and complex architectures out-ran the processing capabilities of a CPU and made way for GPUs which were inherently thought to just be good for processing graphics. The industry was quick to identify the fine-grained parallelism in GPUs’ architecture and utilized it for general purpose computing. GPUs bring in a 10x increase in computing performance and a 5x increase in energy efficiency as the architecture is tolerant of memory latency and has a larger number of transistors dedicated to computation.
The following webinar recording by Wen Phan, Senior Solutions Architect at H2O.ai, discusses the associated enabling technologies, such as CUDA, and demonstrates GPU-expedited performance with the H2O platform, Deep Water.
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