InfoQ Homepage Performance Content on InfoQ
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Practicing at the Cutting Edge: Learning and Unlearning about Java Performance
Martin Thompson overviews Java's evolution, comparing it with C++'s, discussing the challenges of pushing the performance limits.
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How Zynga Handles Monitoring at Scale in Its Hybrid zCloud
Matt West explains how to use technologies like CloudStack, Beanstalk, Gearman, mod_gearman, Nagios, nagconf and other tools to monitor large web applications at scale deployed in the zCloud.
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Machine Learning & Recommender Systems at Netflix Scale
Xavier Amatriain discusses the machine learning algorithms and architecture behind Netflix' recommender systems, offline experiments and online A/B testing.
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Thinking DSLs for Massive Visualization
Leo Meyerovich introduces Superconductor, a browser-based language for massive interactive visualizations using end-to-end parallel DSLs and a synthesis DSL for parallel layout.
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Grails and the Real-time Web
Stephane Maldini on addressing several issues concerning web applications written with Grails: scrolling large data sets without blocking, streaming to the browser, scale Grails in the cloud, etc.
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Native Speed on the Web: JavaScript and asm.js
Alon Zakai discusses asm.js - real-world demos, current limitations, the direction for the future, comparison with other solutions for improving web performance.
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Redesigning PayPal APIs for Scale and Simplicity
Deepak Nadig, Praveen Alavilli present how PayPal redesigned its APIs based on lessons learnt developing their services in over 14 years, and the principles, patterns and anti-patterns used.
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Scaling Pinterest
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
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DevOps Patterns to Scale Web Applications using Cloud Services
Daniel Cukier shares insight in using cloud services to scale web applications, dealing with load balancing, session sharing, email, asynchronous processing, logging, monitoring, CD, RUM, etc.
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Visualization Driven Development
Jason Gilman demonstrates creating visualizations with HTML, CSS, JavaScript, D3, then connect them to a code.
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Graph Computing at Scale
Matthias Broecheler discusses graph computing, introducing the Aurelius graph cluster enabling graph computing at scale by building on distributed systems like Cassandra, HBase, and Hadoop.
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Programming a 144-computer Chip to Minimize Power
Chuck Moore discusses coding techniques for power savings: tight coding to minimize the number of instructions executed, reducing instruction fetches, transistor switching, and duty cycle.
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