Gunrock: A High-Performance Graph Processing Library on the GPU

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We evaluate Gunrock on five key graph primitives and show that Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives, and better performance than any other GPU high-level graph library.Comment: 14 pages, accepted by PPoPP'16 (removed the text repetition in the previous version v5

Splitting hybrid Make-To-Order and Make-To-Stock demand profiles

In this paper a demand time series is analysed to support Make-To-Stock (MTS) and Make-To-Order (MTO) production decisions. Using a purely MTS production strategy based on the given demand can lead to unnecessarily high inventory levels thus it is necessary to identify likely MTO episodes. This research proposes a novel outlier detection algorithm based on special density measures. We divide the time series' histogram into three clusters. One with frequent-low volume covers MTS items whilst a second accounts for high volumes which is dedicated to MTO items. The third cluster resides between the previous two with its elements being assigned to either the MTO or MTS class. The algorithm can be applied to a variety of time series such as stationary and non-stationary ones. We use empirical data from manufacturing to study the extent of inventory savings. The percentage of MTO items is reflected in the inventory savings which were shown to be an average of 18.1%.Comment: demand analysis; time series; outlier detection; production strategy; Make-To-Order(MTO); Make-To-Stock(MTS); 15 pages, 9 figure

Towards a middleware for generalised context management

It is widely accepted in the Pervasive Computing community that contextual interactions are the key to the delivery of truly calm technology. However, there is currently no easy way to incorporate contextual data into an application. If contextual data is used, it is generally in an ad hoc manner, which means that developers have to spend time on low-level details. There have been many projects investigating this area, however as yet none of them provide support for all of the key issues of dynamic composition and flexible representation of contextual information as well as the problems of scalability and adaptability to environmental changes. In this paper we present the Strathclyde Context Infrastructure (SCI), a middleware infrastructure for discovery, aggregation, and delivery of context information