The Computer Science education community is supported by numerous national-focused consortia dedicated to addressing persistent inequalities in student pathways. This panel, comprised of leaders from four of those consortia (CAHSI, STARS, ECEP and RPPforCS) will use four key aspects of improvement communities as a framework for discussing the role, potential and impact of these consortia in supporting the equitable growth of computer science education. While not designed to be Network Improvement Communities per se, we draw upon those frameworks to focus on four specific aspects: 1) guided by shared goals with attention to equity; 2) engaging community in deep understanding of the problems and associated systems; 3) application of improvement science; and 4) coordinated efforts of shared learning and measurements. This will lead towards an open discussion with the audience focused on what has been empirically learned about the value these consortia have for their members and the broader CS Education community.

Computer Science (CS) education has caught a wave -- of media attention, public support, public/private commitments, broad-based participation by educators, and a surge in student enrollments at the undergraduate level. It is a startling change over just the last 5 years. Over that 5 years, much has been accomplished at the high school level. The Exploring Computer Science and Advanced Placement® CS Principles courses were created to engage and inspire a diverse mix of students. Hundreds of teachers and university faculty have collaborated to develop course materials, assessments, MOOCS, and models of teacher professional development. Over 2,000 high schools now offer new CS courses, but that leaves out more than 34,000.

No abstract available.

Our grand challenge is to scale high-quality computer science curriculum and instruction to reach all high school students. CS10K -- an NSF and ACM-sponsored project -- is working to do just that by supporting curriculum development, computer education research and professional development through the Computing Education for the 21st Century (CE21) program at NSF. Professional Development (PD) is a key piece of the project, as we need to train 10,000 teachers to teach rigorous computing courses in 10,000 high schools by 2016 -- the school year that a new Advanced Placement Course will be rolled out. This panel will provide an overview of the PD landscape and then each panelist will discuss the unique aspects of their PD project for high school teachers.

This session will provide information about the current status of Federal budget as it impacts NSF and the computing community. Representatives from both Education and Human Resources (EHR) and Computer and Information Science and Engineering (CISE) directorates will provide the most up-to-date information about available funding opportunities.

The CS Principles Project is a collaborative effort to develop a new introductory course in computer science, accessible to all students. Computer Science educators at all levels have worked together on the development of the new curriculum under the direction of the College Board with support from the National Science Foundation. This special session provides an opportunity for the CS Principles project leaders to report on recent updates and new directions, and to engage in discussion on all aspects of the project with SIGCSE participants

The CS10K project is a large-scale, collaborative project bringing together stakeholders from wide-ranging constituencies with the goal of systematically changing the scale, curriculum, and pedagogy of teaching computer science at all levels, but focusing in particular on computer science in U.S. high schools as well as introductory computing at the college level. As part of the systemic changes in teaching computer science the CS10K project aims to have 10,000 teachers in 10,000 high schools teaching a new curriculum by 2015.

This session highlights programs in the National Science Foundation's (NSF) Education and Human Resources (EHR) and Computer and Information Science and Engineering (CISE) directorates. The focus is on providing descriptions of several programs of interest to college faculty, and discussing the requirements and guidelines for programs in these areas. It includes a description of the proposal and review processes as well as strategies for writing competitive proposals. Participants are encouraged to discuss procedural issues with the presenters.

The Advanced Placement (AP) Computer Science program is intended to reflect enough of a common core of a first semester or year of university-level computer science so that placement or credit can be awarded for work done before college. The SIGCSE symposia have a long history of providing forums for discussing the evolution of the AP program from its inception [1] to the transition from Pascal to C++ [3] to the transition from C++ to Java [2,5,7,8,9]. Panels related to how credit and placement are awarded have also been part of the SIGCSE conferences [4,6]. This special session is a report of the ongoing process of developing new and possible wide-ranging changes to the AP program.

The developers of high-performance scientific applications often work in complex computing environments that place heavy demands on program analysis tools. The developers need tools that interoperate, are portable across machine architectures, and provide source-level feedback. In this paper, we describe a tool framework, the Program Database Toolkit (PDT), that supports the development of program analysis tools meeting these requirements. PDT uses compile-time information to create a complete database of high-level program information that is structured for well-defined and uniform access by tools and applications. PDT’s current applications make heavy use of advanced features of C++, in particular, templates. We describe the toolkit, focussing on its most important contribution -- its handling of templates -- as well as its use in existing applications.

Scientists from many disciplines now routinely use modeling and simulation techniques to study physical and biological phenomena. Advances in high-performance architectures and networking have made it possible to build complex simulations with parallel and distributed interacting components. Unfortunately, the software needed to support such complex simulations has lagged behind hardware developments. We focus here on one aspect of such support: runtime program interaction. We have developed a runtime interaction framework and we have implemented a specific instance of it for an application in seismic tomography. That instance, called TierraLab, extends the geoscientists' existing (legacy) tomography code with runtime interaction capabilities which they access through a MATLAB interface. The scientist can stop a program, retrieve data, analyze and visualize that data with existing MATLAB routines, modify the data, and resume execution. They can do this all within a familiar MATLAB-like environment without having to be concerned with any of the low- level details of parallel or distributed data distribution. Data distribution is handled transparently by the Distributed Array Query and Visualization (DAQV) system. Our framework allows scientists to construct and maintain their own customized runtime interaction system.

The Virtual Notebook Environment (ViNE) is a platform-independent, web-based interface designed to support a range of scientific activities across distributed, heterogeneous computing platforms. ViNE provides scientists with a web-based version of the common paper-based lab notebook, but in addition, it provides support for collaboration and management of computational experiments. Collaboration is supported with the web-based approach, which makes notebook material generally accessible and with a hierarchy of security mechanisms that screen that access. ViNE provides uniform, system-transparent access to data, tools, and programs throughout the scientist's computing infrastructure. Computational experiments can be launched from ViNE using a visual specification language. The scientist is freed from concerns about inter-tool connectivity, data distribution, or data management details. ViNE also provides support for dynamically linking analysis results back into the notebook content. In this paper we present the ViNE system architecture and a case study of its use in neuropsychology research at the University of Oregon. Our case study with the Brain Electrophysiology Laboratory (BEL) addresses their need for data security and management, collaborative support, and distributed analysis processes. The current version of ViNE is a prototype system being tested with this and other scientific applications.

No abstract available.

Techniques that manipulate logical time in order to produce coherent animations of parallel program behavior despite the presence of asynchrony are presented. The techniques interpret program behavior in light of user-defined abstractions and generate animations based on a logical, rather than a physical, view of time. If this interpretation succeeds, the resulting animation is easily understood. If it fails, the programmer can be assured that the failure was not an artifact of the visualization. It is shown that these techniques can be generally applied to enhance visualizations of a variety of types of data as they are produced by parallel, MIMD (multiple instruction stream, multiple data stream) computations.>

Conversion algorithms are presented that would enable programmers to write programs in a high-level, data flow language and then run those programs on a synchronous machine. A model of interprocess communication systems is developed in which both data-driven and synchronous execution modes are represented. Balancing equations are used to characterize a subclass of parallel programs, called loop programs, for which conversions are possible. We show that all loop programs having the finite buffer property can be converted into synchronous mode. Finally two algorithms for the conversion of loop programs are presented and discussed.

A collection of parallel processors is said to be coordinated if each write from one processing element (PE) to another is answered by a read. We report on an efficient algorithm to test coordination for parallel programs in which the code for each PE is a loop. We also test a weaker predicate for parallel algorithms with oblivious PE codes and we show that the general problem is PSPACE-hard.

We present algorithms that convert a class of parallel programs, called loop programs, from data-driven mode to synchronous mode. Such algorithms enable programmers to use a high-level, data-driven programming language without forfeiting the efficiency of a synchronous machine. We characterize loop programs for which conversion is possible in terms of sets of balancing equations and we present two conversion algorithms.