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Scientific Data Bases at Scale and SciDB
by Dr. Stonebraker Michael
Abstract:
As a general rule, scientists have shunned relational data management systems (RDBMS), choosing instead to “roll their own” on top of file system technology. We first discuss why file systems are a poor choice for science data storage, especially as data volumes become large and scalability becomes important.
Then, we continue with the reasons why RDBMSs work poorly on most science applications. These include a data model “impedance mismatch&r...
Abstract:
As a general rule, scientists have shunned relational data management systems (RDBMS), choosing instead to “roll their own” on top of file system technology. We first discuss why file systems are a poor choice for science data storage, especially as data volumes become large and scalability becomes important.
Then, we continue with the reasons why RDBMSs work poorly on most science applications. These include a data model “impedance mismatch” and missing features. We discuss array DBMSs, and why they are a much better choice for science applications, and use SciDB as an exemplar of this new class of DBMSs.
Most science applications require a mix of data management and complex analytics. In most cases, the analytics entail a sequence of linear algebra computations. We discuss the possible ways of integrating a DBMS with statistical calculations, and conclude with the mechanism being used by SciDB.
Bio:
Dr. Stonebraker has been a pioneer of data base research and technology for more than a quarter of a century. He was the main architect of the INGRES relational DBMS, and the object-relational DBMS, POSTGRES. These prototypes were developed at the University of California at Berkeley where Stonebraker was a Professor of Computer Science for twenty five years. More recently at M.I.T. he was a co-architect of the Aurora/Borealis stream processing engine, the C-Store column-oriented DBMS, and the H-Store transaction processing engine. Currently, he is working on science-oriented DBMSs, OLTP DBMSs, and scalable data curation. He is the founder of five venture-capital backed startups, which commercialized his prototypes. Presently he serves as Chief Technology Officer of VoltDB and Paradigm4, Inc.
Professor Stonebraker is the author of scores of research papers on data base technology, operating systems and the architecture of system software services. He was awarded the ACM System Software Award in 1992, for his work on INGRES. Additionally, he was awarded the first annual Innovation award by the ACM SIGMOD special interest group in 1994, and was elected to the National Academy of Engineering in 1997. He was awarded the IEEE John Von Neumann award in 2005, and is presently an Adjunct Professor of Computer Science at M.I.T, where he is co-director of the new Intel Science and Technology Center focused on big data.
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Recent results on SUSY searches from CMS
by Hooberman Benjamin Henry
The latest results on searches for Supersymmetry from CMS are reviewed. We present searches for direct stop production, searches in final states with four W bosons and multiple b-quarks, and searches for R-Parity violating SUSY. The results use up to 20/fb of data from the 8 TeV LHC run of 2012.
The latest results on searches for Supersymmetry from CMS are reviewed. We present searches for direct stop production, searches in final states with four W bosons and multiple b-quarks, and searches for R-Parity violating SUSY. The results use up to 20/fb of data from the 8 TeV LHC run of 2012.
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Hidden in the Clouds: New Ideas in Cloud Computing
by Dr. Shevek
Abstract:
Cloud computing has become a hot topic. But 'cloud' is no newer in 2013 than MapReduce was in 2005: We've been doing both for years. So why is cloud more relevant today than it ever has been?
In this presentation, we will introduce the (current) central thesis of cloud computing, and explore how and why (or even whether) the concept has evolved.
While we will cover a little light background, our primary focus will be on the consequences, corollaries and techniques...
Hidden in the Clouds: New Ideas in Cloud Computing
Abstract:
Cloud computing has become a hot topic. But 'cloud' is no newer in 2013 than MapReduce was in 2005: We've been doing both for years. So why is cloud more relevant today than it ever has been?
In this presentation, we will introduce the (current) central thesis of cloud computing, and explore how and why (or even whether) the concept has evolved.
While we will cover a little light background, our primary focus will be on the consequences, corollaries and techniques introduced by some of the leading cloud developers and organizations.
We each have a different deployment model, different applications and workloads, and many of us are still learning to efficiently exploit the platform services offered by a modern implementation. The discussion will offer the opportunity to share these experiences and help us all to realize the benefits of cloud computing to the fullest degree.
Please bring questions and opinions, and be ready to share both!
Bio:
Shevek is a principal architect at Nebula, and an expert programmer with a strong interest in parallel and distributed systems. He has worked on cutting edge research in compilers and language design, algorithmic optimization, systems and security. He is capable of maintaining a very straight face under questioning on topics including
“Why is our printer playing ‘happy birthday’?” or “What is that message doing on the side of that building?” He received a Doctorate in Computing on the Formalization of Protection Systems from the University of Bath, England. He also holds a Masters in Pure Mathematics and fences epee.
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