27 citations · 130 across the 16 of their papers we have counts for
18 papers
Matrix Multiplication Using Only Addition
Daniel Cussen, Jeffrey D. Ullman
Matrix multiplication consumes a large fraction of the time taken in many machine-learning algorithms. Thus, accelerator chips that perform matrix multiplication faster than conven…
Panda: Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data
Sharad Mehrotra, Shantanu Sharma, Jeffrey D. Ullman +2
Despite extensive research on cryptography, secure and efficient query processing over outsourced data remains an open challenge. This paper continues along with the emerging trend…
Efficient Multiway Hash Join on Reconfigurable Hardware
Kunle Olukotun, Raghu Prabhakar, Rekha Singhal +2
We propose the algorithms for performing multiway joins using a new type of coarse grain reconfigurable hardware accelerator~-- ``Plasticine''~-- that, compared with other accelera…
Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data
Sharad Mehrotra, Shantanu Sharma, Jeffrey D. Ullman +1
Despite extensive research on cryptography, secure and efficient query processing over outsourced data remains an open challenge. This paper continues along the emerging trend in s…
Efficient and Private Approximations of Distributed Databases Calculations
Philip Derbeko, Shlomi Dolev, Ehud Gudes +1
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 sepa…
Some Pairs Problems
Jeffrey D. Ullman, Jonathan Ullman
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 w…