Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science

Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters

General purpose computing on graphics processing units (GPGPU) is dramatically changing the landscape of high performance computing in astronomy. In this paper, we identify and investigate several key decision areas, with a goal of simplyfing the early adoption of GPGPU in astronomy. We consider the merits of OpenCL as an open standard in order to reduce risks associated with coding in a native, vendor-specific programming environment, and present a GPU programming philosophy based on using brute force solutions. We assert that effective use of new GPU-based supercomputing facilities will require a change in approach from astronomers. This will likely include improved programming training, an increased need for software development best-practice through the use of profiling and related optimisation tools, and a greater reliance on third-party code libraries. As with any new technology, those willing to take the risks, and make the investment of time and effort to become early adopters of GPGPU in astronomy, stand to reap great benefits.Comment: 13 pages, 5 figures, accepted for publication in PAS

An evaluation of a professional learning network for computer science teachers

This paper describes and evaluates aspects of a professional development programme for existing CS teachers in secondary schools (PLAN C) which was designed to support teachers at a time of substantial curricular change. The paper’s particular focus is on the formation of a teacher professional development network across several hundred teachers and a wide geographical area. Evidence from a series of observations and teacher surveys over a two-year period is analysed with respect to the project’s programme theory in order to illustrate not only whether it worked as intended, by why. Results indicate that the PLAN C design has been successful in increasing teachers’ professional confidence and appears to have catalysed powerful change in attitudes to learning. Presentation of challenging pedagogical content knowledge and conceptual frameworks, high-quality teacher-led professional dialogue, along with the space for reflection and classroom trials, triggered examination of the teachers’ own current practices

Achieving Efficient Strong Scaling with PETSc using Hybrid MPI/OpenMP Optimisation

The increasing number of processing elements and decreas- ing memory to core ratio in modern high-performance platforms makes efficient strong scaling a key requirement for numerical algorithms. In order to achieve efficient scalability on massively parallel systems scientific software must evolve across the entire stack to exploit the multiple levels of parallelism exposed in modern architectures. In this paper we demonstrate the use of hybrid MPI/OpenMP parallelisation to optimise parallel sparse matrix-vector multiplication in PETSc, a widely used scientific library for the scalable solution of partial differential equations. Using large matrices generated by Fluidity, an open source CFD application code which uses PETSc as its linear solver engine, we evaluate the effect of explicit communication overlap using task-based parallelism and show how to further improve performance by explicitly load balancing threads within MPI processes. We demonstrate a significant speedup over the pure-MPI mode and efficient strong scaling of sparse matrix-vector multiplication on Fujitsu PRIMEHPC FX10 and Cray XE6 systems

Brain Resilience: Shedding Light into the Black Box of Adventure Processes

Understanding of the active beneficial processes of adventure learning remains elusive. Resilience may provide one foundation for understanding the positive adaptation derived from Outdoor Adventure Education (OAE) and Adventure Therapy (AT) programming. From a neurological perspective, resilience may be explained by the brain’s innate capability to adapt its structure (growth of new cells) and function (re-wiring of existing cells) directly in response to environmental exposure. This paper explores the role of known brain responses to experiences analogous to adventure programming based on themes from a key literature review. The fundamental paradigm of ‘stress and recovery’ contends that a balance of neurobiological processes help realign psychosocial equilibrium in the short term and over time. Through progressive, repeated exposure to custom-built outdoor challenges, the concept of brain resilience may provide a scientific platform for understanding the mechanisms of achieving meaningful, authentic and healthy outcomes. It could also help to begin to illuminate a section of the black box of adventure processes