A Look at Conflict-Free Replicated Data Types (CRDT)
You may have heard about CRDTs in the past few years if you are into distributed systems. In this post I will give a brief summary of what they are and what kind of guarantees they provide. In short, CRDTs are objects that can be updated without expensive synchronization/consensus and they are guaranteed to converge eventually if all concurrent updates are commutative (see below) and if all update
Apache SystemML
SystemML is now SystemDS To reflect the change of focus to the end-to-end data science lifecycle What is SystemDS? SystemDS is an open source ML system for the end-to-end data science lifecycle from data integration, cleaning, and feature engineering, over efficient, local and distributed ML model training, to deployment and serving. To this end, it provides a stack of declarative languages with R
Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective - Meta Research | Meta Research
Applied Machine Learning at Facebook: A Datacenter Infrastructure PerspectiveInternational Symposium on High-Performance Computer Architecture (HPCA) Machine learning sits at the core of many essential products and services at Facebook. This paper describes the hardware and software infrastructure that supports machine learning at global scale. Facebook’s machine learning workloads are extremely d
[1712.01208] The Case for Learned Index Structures
Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be
ML Systems
Workshop on ML Systems at NIPS 2017 December 8, 2017 Home Call for Papers Schedule Speakers Accepted Papers ML Systems Workshop A new area is emerging at the intersection of artificial intelligence, machine learning, and systems design. This birth is driven by the explosive growth of diverse applications of ML in production, the continued growth in data volume, and the complexity of large-scale le
Google Vizier: A Service for Black-Box Optimization
Daniel Golovin (Google, Inc.);Benjamin Solnik (Google, Inc.);Subhodeep Moitra (Google, Inc.);Greg Kochanski (Google, Inc.);John Karro (Google, Inc.);D. Sculley (Google, Inc.) Abstract Any sufficiently complex system acts as a black box when it becomes easier to experiment with than to understand. Hence, black-box optimization has become increasingly important as systems have become more complex. I
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
https://www.sysml.cc/doc/40.pdf
http://www.sysml.cc/doc/37.pdf
WideTable: An Accelerator for Analytic Data Processing
http://pages.cs.wisc.edu/~jignesh/publ/WideTable.pdf
https://www.sysml.cc/doc/49.pdf
CSE 291A: Advanced Data Analytics and ML Systems
SIGMOD Tutorial 9, Friday May 19, 9 AM
CSE 291A: Advanced Data Analytics and ML Systems
Schedule
John Oliver indicates infrastructure is not sexy but it is important | NextBigFuture.com
http://www.vldb.org/pvldb/vol11/p746-yin.pdf
Sang-Won Lee
http://www.vldb.org/pvldb/vol11/p975-bellomarini.pdf
http://www.vldb.org/pvldb/vol11/p787-ding.pdf
http://www.sysml.cc/doc/9.pdf
http://learningsys.org/nips17/assets/papers/paper_32.pdf
http://learningsys.org/nips17/assets/papers/paper_22.pdf
http://learningsys.org/nips17/assets/papers/paper_19.pdf
http://learningsys.org/nips17/assets/papers/paper_14.pdf
TensorFlow Dev Summit
TensorFlow Extended (TFX) (TensorFlow Dev Summit 2018)
http://learningsys.org/nips17/assets/papers/paper_11.pdf
http://learningsys.org/nips17/assets/papers/paper_1.pdf
Enabling Full Stack Data Scientists at Stitch Fix
https://www.sysml.cc/doc/23.pdf
SysML Conference
Eric Breck's homepage