Winnie Wang

Although pioneering studies using statistical methods in geographical data analysis were published in the 1930s, it was only in the 1960s that their increasing use in human geography led to a claim that a ‘quantitative revolution’ had taken place. The widespread use of quantitative methods from then on was associated with changes in both disciplinary philosophy and substantive focus. The first decades of the ‘revolution’ saw quantitative analyses focused on the search for spatial order of a geometric form within an, often implicit, logical positivist framework. In the first of three reviews of the use of quantitative methods in human geography, this progress report uncovers their origin with regard to the underlying philosophy, the focus on spatial order, and the nature of the methods deployed. Subsequent reports will outline the changes in all three that occurred in later decades and will chart the contemporary situation.

ABSTRACT: Magnetic fusion is a long-term solution for producing electrical power for the world, and the large thermonuclear international device being constructed will produce net energy and a path to fusion energy provided the computer modeling is accurate. To effectively address the requirements of the high-end fusion simulation community, application developers, algorithm designers, and hardware architects must have reliable simulation data gathered at scale for scientifically valid configurations. This paper presents detailed benchmarking results for a set of magnetic fusion applications with a wide variety of underlying mathematical models including both particle-in-cell and Eulerian codes using both implicit and explicit numerical solvers. Our evaluation on a petascale Cray XE6 platform focuses on profiling these simulations at scale identifying critical performance characteristics, including scalability, memory/network bandwidth limitations, and communication overhead. Overall results are a key in improving fusion code design, and are a critical first step towards exascale hardware-software co-design — a process that tightly couples applications, algorithms, imple- mentation, and computer architecture.