A Scalable General Purpose System for Large-Scale Graph Processing

Graph analytics is an important and computationally demanding class of data analytics. It is essential to balance scalability, ease-of-use and high performance in large scale graph analytics. As such, it is necessary to hide the complexity of parallelism, data distribution and memory locality behind an abstract interface. The aim of this work is to build a scalable graph analytics framework that does not demand significant parallel programming experience based on NUMA-awareness.
The realization of such a system faces two key problems:
(i)~how to develop a scale-free parallel programming framework that scales efficiently across NUMA domains; (ii)~how to efficiently apply graph partitioning in order to create separate and largely independent work items that can be distributed among threads.

Molecular Recognition in Biomimetic Receptors

This book commemorates the 25th anniversary of the International Izatt-Christensen Award in Macrocyclic and Supramolecular Chemistry. The award, one of the most prestigious of small awards in chemistry, recognizes excellence in the developing field of macrocyclic and supramolecular chemistry

Macrocyclic and Supramolecular Chemistry: How Izatt-Christensen Award Winners Shaped the Field features chapters written by the award recipients who provide unique perspectives on the spectacular growth in these expanding and vibrant fields of chemistry over the past half century, and on the role of these awardees in shaping this growth. During this time there has been an upsurge of interest in the design, synthesis and characterization of increasingly more complex macrocyclic ligands and in the application of this knowledge to understanding molecular recognition processes in host-guest chemistry in ways that were scarcely envisioned decades earlier.