Papers We Love is a repository of academic computer science papers and a community who loves reading them.
Chapters:
- Seattle
- San Francisco
- New York
- Columbus
- Chattanooga
- London
- Vienna
- Montreal
- St. Louis
- Washington, DC
- San Diego
- Bangalore
- Toronto
- Singapore
- Brasilia
- Pune
- Los Angeles
- Boston
- Denver
- Rio de Janeiro
- Berlin
- Belfast
- Bucharest
- Winnipeg
- Madrid
- Athens
- Chicago
- Porto
- Hyderabad
- Amsterdam
- Gothenburg
- Munich
- Barcelona
- Utrecht
- Philadelphia
- Zürich
- Portland
- Raleigh-Durham
- Lebanon
- Teresina
- Hamburg
- Budapest
- Kyiv
- Reykjavik
- Kansas City
- Buenos Aires
- Seoul
- Kathmandu
- Guadalajara
- Cairo
- Mumbai
- Beijing
- Milano
Henry Robinson on No compromises: distributed transactions with consistency, availability, and performance
Gorka Guardiola on Paths, Trees and Flowers
January Meetups
We have another great line-up of meet-ups scheduled for January across a number of our chapters:
Bangalore 1/2: Shor's Algorithm Part
Bangalore 1/9: Shor's Algorithm Part
Bucharest 1/11: January Meetup
Vienna 1/14: Lisp
Seattle 1/14: : The Dataflow Model and Millwheel: Fault tolerant stream processing
Bangalore 1/17: Meet Dr. Shriram Krishnamurthi
Saint Louis 1/18: Magnetic Levitation & Guidance
Madrid 1/20: Path, Trees and Flowers
London 1/20: Tom Crayford on 'An History and Evaluation of System R'
Montréal 1/20: Better Bitmap Performance with Roaring Bitmaps
Winnipeg 1/20: Communication in the Presence of Noise
San Francisco 1/21: Henry Robinson on "No compromises: distributed transactions with consistency.."
Seattle 1/27: .: Scalable Atomic Visibility with RAMP Transactions
Marina del Rey 1/27: Bill Berry on No Silver Bullet
New York 1/28: Ramsey Nasser on PushPull++
Nathan Taylor / Chris Meiklejohn on OS Scalability & Chain Replication
The Papers: Christopher Meiklejohn's A Brief History of Chain Replication
Meetup Spotlight: http://bit.ly/1QelqoU
On December 10, 2015, Christopher Meikljohn is presenting at Papers We Love - San Francisco on the topic (and history) of Chain Replication, a data replication technique that "promises a high throughput, linearizable, robust replication technique with minimal overhead to tolerate failures with only f+1 nodes[0]."