Andy Konwinski

Computer Networks and Communications · 2008–2018

A researcher in the Science corpus: 8 papers; trusts 5 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Networks and Communications — 40 citations into it; #8,526 of 9,886 by trust here, #440 by citations
• Information Systems — 32 citations into it; #7,327 of 8,771 by trust here, #373 by citations
• Hardware and Architecture — 16 citations into it; #1,244 of 1,551 by trust here, #494 by citations
• ML Systems & Hardware — 12 citations into it; #485 of 575 by trust here, #68 by citations
• Artificial Intelligence — 9 citations into it

Whom Andy Konwinski trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Muthu Dayalan
2. Matei A. Zaharia
3. David Ruppert
4. Daniel Peng
5. Hervé Moulin
6. Michael Isard
7. Grzegorz Malewicz

Who trusts Andy Konwinski overall

1. Christina Delimitrou
2. Mosharaf Chowdhury
3. Ganesh Ananthanarayanan
4. Kay Ousterhout
5. Christos Kozyrakis
6. Francesco Pace
7. Simon Shillaker
8. Lida Xu
9. Matei A. Zaharia
10. Jimmy J. Lin

Papers from Andy Konwinski's perspective

Ordered by how strongly the researchers Andy Konwinski trusts endorse each paper. Same corpus, a different order for every researcher.

1. MapReduce: simplified data processing on large clusters
2. Pregel: a system for large-scale graph processing (SIGMOD Conference)
3. Spark: Cluster Computing with Working Sets
4. Quincy: fair scheduling for distributed computing clusters (Symposium on Operating Systems Principles)
5. Design and Implementation of a General Purpose Parallel Programming System
6. Et al
7. Distributed computing in practice: the Condor experience (Concurrency Practice and Experience)
8. Twister: a runtime for iterative MapReduce (IEEE International Symposium on High-Performance Parallel Distributed Computing)
9. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
10. Improving MapReduce Performance in Heterogeneous Environments

Their papers

• Accelerating the Machine Learning Lifecycle with MLflow (2018) — 559 citations
• Learning Spark: Lightning-Fast Big Data Analytics (2015) — 354 citations
• Omega: flexible, scalable schedulers for large compute clusters (2013) — 789 citations
• Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center (2011) — 2,075 citations
• Dominant Resource Fairness: Fair Allocation of Multiple Resource Types (2011) — 1,398 citations
• A view of cloud computing (2010) — 10,800 citations
• Above the Clouds: A Berkeley View of Cloud Computing (2009) — 7,476 citations
• Improving MapReduce Performance in Heterogeneous Environments (2008) — 1,941 citations