Data-Parallel Hashing Techniques for GPU Architectures

Probabilistic Hashing Techniques for Big Data

Optimal Expression Evaluation for Data Parallel Architectures

A data parallel machine represents an array or other composite data structure by allocating one processor (at least conceptually) per data item. A pointwise operation can be performed between two such arrays in unit time, provided their corresponding elements are allocated in the same processors. If the arrays are not aligned in this fashion, the cost of moving one or both of them is part of th...

Parallel Architectures and Compilation Techniques PACT 2001

Foreword This year's International Conference on Parallel Architectures and Compilation Techniques (PACT 2001) includes for the first time a Work-in-Progress session. We received many excellent short abstracts – some of which were wild ideas. From these we chose seven abstracts for presentation, and we have included them in this booklet. We selected them for their novelty and the brevity with w...

Designing OP2 for GPU architectures

OP2 is an “active” library framework for the solution of unstructured mesh applications. It aims to decouple the specification of a scientific application from its parallel implementation to achieve code longevity and near-optimal performance through re-targeting the back-end to different multi-core/many-core hardware. This paper presents the design of the current OP2 library for generating eff...

Hybrid Use of Hashing Techniques for Spatial Data

Hashing techniques are reviewed that are applicable to the organization and indexing of spatial data. An adaptive file organization scheme for polygon data is presented that is based on extendable hashing and interpolation-based index maintenance. This scheme aims to locate a record with a given key using an average of one disk access, and at most two. It also aims to process search by location...