Cliff Click

👥 1 conference
🎤 1 talk
📅 Years active: 2016 to 2016

Biography

Coding for 40 years. Worked on the core guts of HotSpot, the JVM. 20 patents, dozen publications, hundreds of public speaking events.

Cliff Click is the CTO and Co-Founder of H2O, makers of H2O, the opensource math and machine learning engine for Big Data. Cliff wrote his first compiler when he was 15 (Pascal to TRS Z-80!), although Cliff’s most famous compiler is the HotSpot Server Compiler (the Sea of Nodes IR). Cliff helped Azul Systems build an 864 core pure-Java mainframe that keeps GC pauses on 500Gb heaps to under 10ms, and worked on all aspects of that JVM.

Before that he worked on HotSpot at Sun Microsystems, and was at least partially responsible for bringing Java into the mainstream. Cliff is invited to speak regularly at industry and academic conferences and has published many papers about HotSpot technology. He holds a PhD in Computer Science from Rice University and about 20 patents.

— biography from FOSDEM 2016
https://archive.fosdem.org/2016/schedule/speaker/cliff_click/

Conferences

1 known conferences

👥 FOSDEM 2016 📅 30 Jan 2016

🎤 H2O: An Open-Source Platform for Machine Learning and Big Data/Big Math
30 Jan 2016 show details

This is a technical talk on the insides of H2O, specifically focusing on the Single-System-Image aspect: how we write single-threaded code, and have H2O auto-parallelize and auto-scale-out to 100's of nodes and 1000's of cores.

H2O: An Open-Source Platform for Machine Learning and Big Data/Big Math. H2O is clustering: from just your laptop to 100's of nodes, you get a Single System Image; allowing easy aggregation of all the memory and all the cores, and a simple coding style that scales wide at in-memory speeds. H2O is easily 1000x faster than disk based clustering solutions, and often 10x faster than best-of-breed alternative in-memory solutions. H2O is Big Data: we ingest a wide variety of formats, in parallel and distributed across the cluster, and store the data column-compressed - often exceeding 2x to 4x gzip-on-disk. H2O is Big Math: we do scale-out math at memory-bandwidth speeds (on compressed data!), making terabyte-scale munging an interactive experience. H2O is Machine Learning: On this Big Data, Big Math platform we have Best-of-Breed implementations of effective and popular Machine Learning algorithms: e.g. Deep Learning (Neural Nets), GBM, Random Forest, GLM, K-means, PCA, Naive Bayes, and more... with all the features you need to do real data science built-in. Finally H2O interacts directly with Python, R, Scala, Spark, REST/JSON, and a JS-based web browser - making it the most interconnected Machine Learning platform out there.