Scale By The Bay 2018: Cliff Click, H2O internals

ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Scale By the Bay 2019 is held on November 13-15 in sunny Oakland, California, on the shores of Lake Merritt: https://scale.bythebay.io. Join us! ----- H2O does in-memory analytics on clusters with distributed parallelized state-of-the-art Machine Learning algorithms. However, the platform is very generic, and very very fast. H2O.ai builds Machine Learning tools with it, but the platform can do much more. H2O includes a K/V store exact semantics with typical read and write speeds of ~200ns; a highly compressed Big Data in-memory storage typically better than 2x to 4x gzip-on-disk size, which can read and decompress the data at C/Fortran speed; a pure-Java clean and simple coding style to write parallel & distributed code; a generic serializer that's well faster than protobuf or kryo and does not need an special registration or markup language; a large set of building blocks for common math operations, and of course a library of state-of-the-art ML algorithms. This is a low-level systems' implementation talk of H2O's design.

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