Jeffrey D. Ullman
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View article: Champhibians, a citizen science programme for schools: a project introduction and case study from Malls Mire Local Nature Reserve in Glasgow, Scotland
Champhibians, a citizen science programme for schools: a project introduction and case study from Malls Mire Local Nature Reserve in Glasgow, Scotland Open
Champhibians, the “champions of amphibians,” a pond adoption project instigated by Amphibian and Reptile Conservation (ARC), provides an interesting case-study of a citizen science project that was specifically designed for schools. This p…
View article: Matrix Multiplication Using Only Addition
Matrix Multiplication Using Only Addition Open
Matrix multiplication consumes a large fraction of the time taken in many machine-learning algorithms. Thus, accelerator chips that perform matrix multiplication faster than conventional processors or even GPU's are of increasing interest.…
View article: Abstractions, their algorithms, and their compilers
Abstractions, their algorithms, and their compilers Open
Jeffrey D. Ullman and Alfred V. Aho are recipients of the 2020 ACM A.M. Turing award. They were recognized for creating fundamental algorithms and theory underlying programming language implementation and for synthesizing these results and…
View article: Efficient Multiway Hash Join on Reconfigurable Hardware
Efficient Multiway Hash Join on Reconfigurable Hardware Open
We propose the algorithms for performing multiway joins using a new type of coarse grain reconfigurable hardware accelerator~-- ``Plasticine''~-- that, compared with other accelerators, emphasizes high compute capability and high on-chip c…
View article: Scaling Cryptographic Techniques by Exploiting Data Sensitivity at a Public Cloud
Scaling Cryptographic Techniques by Exploiting Data Sensitivity at a Public Cloud Open
Despite extensive research on cryptography, secure and efficient query processing over outsourced data remains an open challenge. This poster continues along the emerging trend in secure data processing that recognizes that the entire data…
View article: Efficient and private approximations of distributed databases calculations
Efficient and private approximations of distributed databases calculations Open
In recent years, an increasing amount of data is collected in different and often, not cooperative, databases. The problem of privacy-preserving, distributed calculations over separated databases and, a relative to it, issue of private dat…
View article: Shasta
Shasta Open
We describe Shasta, a middleware system built at Google to support interactive reporting in complex user-facing applications related to Google's Internet advertising business. Shasta targets applications with challenging requirements: Firs…
View article: Some Pairs Problems
Some Pairs Problems Open
A common form of MapReduce application involves discovering relationships between certain pairs of inputs. Similarity joins serve as a good example of this type of problem, which we call a "some-pairs" problem. In the framework of Afrati e…
View article: It's All a Matter of Degree: Using Degree Information to Optimize Multiway Joins
It's All a Matter of Degree: Using Degree Information to Optimize Multiway Joins Open
We optimize multiway equijoins on relational tables using degree information. We give a new bound that uses degree information to more tightly bound the maximum output size of a query. On real data, our bound on the number of triangles in …
View article: Computing Marginals Using MapReduce
Computing Marginals Using MapReduce Open
We consider the problem of computing the data-cube marginals of a fixed order $k$ (i.e., all marginals that aggregate over $k$ dimensions), using a single round of MapReduce. The focus is on the relationship between the reducer size (numbe…
View article: Meta-MapReduce: A Technique for Reducing Communication in MapReduce Computations
Meta-MapReduce: A Technique for Reducing Communication in MapReduce Computations Open
MapReduce has proven to be one of the most useful paradigms in the revolution of distributed computing, where cloud services and cluster computing become the standard venue for computing. The federation of cloud and big data activities is …
View article: Assignment Problems of Different-Sized Inputs in MapReduce
Assignment Problems of Different-Sized Inputs in MapReduce Open
A MapReduce algorithm can be described by a mapping schema, which assigns inputs to a set of reducers, such that for each required output there exists a reducer that receives all the inputs that participate in the computation of this outpu…
View article: Handling Skew in Multiway Joins in Parallel Processing
Handling Skew in Multiway Joins in Parallel Processing Open
Handling skew is one of the major challenges in query processing. In distributed computational environments such as MapReduce, uneven distribution of the data to the servers is not desired. One of the dominant measures that we want to opti…
View article: Assignment of Different-Sized Inputs in MapReduce
Assignment of Different-Sized Inputs in MapReduce Open
A MapReduce algorithm can be described by a mapping schema, which assigns inputs to a set of reducers, such that for each required output there exists a reducer that receives all the inputs that participate in the computation of this outpu…