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09:41

Cybertron: Pushing the Limit on I/O Reduction in Data-Parallel Programs

Posted by Tian Xiao, Jiaxing Zhang, Chencheng Ye, Wenguang Chen, Zhenyu Guo, Hucheng Zhou, Xu Zhao, Xi Wang, Wei Lin, Lidong Zhou  on  May 29, 2015

The authors introduce Cybertron, a new tool for reducing I/O operations in data-parallel programs through a constraint-based encoding.

18:19

ASPIRE:Exploiting Asynchronous Parallelism in Iterative Algorithms using a Relaxed Consistency-based DSM

Posted by Keval Vora, Sai Charan Koduru, Rajiv Gupta  on  May 14, 2015

The authors present a relaxed memory consistency model and consistency protocol that tolerate communication latency and minimize the use of stale values, outperforming other models.

47:55

The Quest for the One True Parser

Posted by Terence Parr  on  Feb 15, 2015 1

Terence Parr shows the key practical advances in parsing from the last 25 years, provides algorithm comparisons, and separates the promises from reality.

43:55

Not Exactly! Fast Queries via Approximation Algorithms

Posted by Fangjin Yang, Nelson Ray  on  Jan 20, 2015

Fangjin Yang, creator of Druid, shows how approximation algorithms can help system scale out linearly and process huge amount of data quickly with small memory footprint.

43:56

Machine Learning at Netflix Scale

Posted by Aish Fenton  on  Oct 07, 2014 4

Aish Fenton discusses Netflix' machine learning algorithms, including distributed Neural Networks on AWS GPUs, providing insight into offline experimentation and online AB testing.

01:18:44

Order Notation in Practice

Posted by Roger Orr  on  Jun 18, 2014 1

Roger Orr solves a problem with different levels of complexity trying to answer what the complexity notation actually means and why it is important in practice.

42:59

Revealing the Uncommonly Common with Elasticsearch

Posted by Mark Harwood  on  Apr 08, 2014

Mark Harwood shows how anomaly detection algorithms can spot card fraud, incorrectly tagged movies and the UK's most unexpected hotspot for weapon possession.

38:16

Top 10 Performance Gotchas in Scaling In-memory Algorithms

Posted by SriSatish Ambati  on  Mar 20, 2014

SriSatish Ambati shares tips for in-memory algorithms, discussing I/O, S3 resets, muxers, primitive byte arrays, non-blocking structures, and fork/join queues.

41:14

Machine Learning & Recommender Systems at Netflix Scale

Posted by Xavier Amatriain  on  Jan 16, 2014

Xavier Amatriain discusses the machine learning algorithms and architecture behind Netflix' recommender systems, offline experiments and online A/B testing.

51:53

Lock-Free Algorithms For Ultimate Performance

Posted by Martin Thompson  on  Apr 02, 2013

Martin Thompson discusses the need to measure what’s going on at the hardware level in order to be able to create high performing lock-free algorithms.

The Algorithms Still Count

Posted by Shawn Wallace  on  Jul 13, 2012 2

Shawn Wallace takes a look at several problems explaining how to evaluate possible solutions and to compare with each other.

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