This is an introduction to creative software development and music making in Python. This material is intended for CS0/CS1 courses and for courses at the intersection of computing and the arts. The workshop will introduce music making activities for teaching traditional CS1 topics, GUIs, event-driven programming, and connecting to external devices (e.g., smartphones, digital pianos) via MIDI and OSC (Open Sound Control). Participants will be introduced to Jython Music (http://jythonMusic.org), a library of Python modules for creative programming and music making, and will be making their own music artifacts a few minutes later. Intended audience: Computer science educators interested in teaching creative programming and computational thinking for CS0, CS1, introductory courses in the intersection of computing and the arts, and courses intended to attract and retain new CS majors. Each participant will receive a copy of (1) handouts to be used during the workshop, (2) sample student assignments and projects, (3) API documentation, (4) all required software, and (5) numerous sample programs. Laptop required (with Java JDK 7 or higher). All other software will be provided. Headphones are recommended.

What design factors contribute to an illusion of agency in a computational system? Our previous research [1, 2] has investigated this question in the context of creative human-machine musical partnerships, where we identified musical behaviours implying machine agency from the perspective of a human performer. This paper investigates an audience perspective: what factors contribute to an impression of machine agency for in a musical performance? Audience feedback data was collected during a concert with four performances, each comprising a human musician interacting with a computer music system. Three performances utilized a computational agent, CIM [1], designed for this research. The fourth performance utilized an array of effect pedals designed in an extended instrument paradigm [3]. The audience feedback questionnaire queried whether a sense of machine agency was imparted, and to what degree visual, spatial, timbral and musical factors contributed to this impression. The results showed our CIM system succeeded in imparting a sense of agency, and that all four of the suggested factors contributed to that impression.

We report a systematic study on the impact of process and statistical variability on SRAM design in a 14nm SOI FinFET technology node. A comprehensive statistical compact modelling strategy is developed for the early delivery of reliable PDK model, which enables TCAD-based transistor-cell co-design and path finding during the early phase of a technology node.

A set of analytical models based on the Pearson distribution function applied to the modeling of ion implantations in the 3-D structure of FinFETs is presented. The method provides a succinct way to simulate the doping profiles in FinFETs at low computational cost. Compared to previous analytical methods based on Gaussian distributions, this approach handles more realistic asymmetrical doping distributions arising from ion implantation. A simulation module in C++ has been developed to model ion implantations in FinFETs based on this analytical approach. The simulation module is demonstrated in an example simulation of a silicon-on-insulator FinFET with physical gate length of 20 nm.

Quantitative simulations of the statistical impact of negative-bias-temperature-instability (NBTI) on pMOSFETs, and positive-bias-temperature-instability (PBTI) on nMOSFETs are carried out for a 45nm low power technology generation. Based on the statistical simulation results, we investigate the impact of NBTI and PBTI on the degradation of the static noise margin (SNM) of SRAM cells. The results indicate that SNM degradation due only to NBTI follows a different evolution pattern compared with the impact of simultaneous NBTI and PBTI degradation.

The TRAMS (Terascale Reliable Adaptive MEMORY Systems) project addresses in an evolutionary way the ultimate CMOS scaling technologies and paves the way for revolutionary, most promising beyond-CMOS technologies. In this abstract we show the significant variability levels of future 18 and 13nm device bulk-CMOS technologies as well as its dramatic effect on the yield of memory cells, and what kind of circuit solution would be required to maintain the current yield level. Later, we discuss the impact of errors at the system level, and different approaches at system level to adapt the heterogeneous systems to user's requirements.

Dynamic software systems for generative art have particular requirements around rapid development and manipulation of ideas and real-time computational processes. Impromptu is an innovative new programming environment created by Andrew Sorensen, and is designed to facilitate the fluid flow of creative ideas and their expression in software. It has been used for our recent projects, including a variety of Collaborative Music Jamming Systems, because it supports creative processes by leveraging the audio, graphic and video capabilities of the modern operating system within a dynamic programming environment. In our projects collaboration is supported through a synthesis of media types, numerous communication protocols, and facilities for inter-system communications and control. The demonstration will show these environments and how Impromptu supported their development.

We present a hierarchical approach to the "atomistic" simulation of aggressively scaled sub-0.1-/spl mu/m MOSFETs. These devices are so small that their characteristics depend on the precise location of dopant atoms within them, not just on their average density. A full-scale three-dimensional drift-diffusion atomistic simulation approach is first described and used to verify more economical, but restricted, options. To reduce processor time and memory requirements at high drain voltage, we have developed a self-consistent option based on a solution of the current continuity equation restricted to a thin slab of the channel. This is coupled to the solution of the Poisson equation in the whole simulation domain in the Gummel iteration cycles. The accuracy of this approach is investigated in comparison to the full self-consistent solution. At low drain voltage, a single solution of the nonlinear Poisson equation is sufficient to extract the current with satisfactory accuracy. In this case, the current is calculated by solving the current continuity equation in a drift approximation only, also in a thin slab containing the MOSFET channel. The regions of applicability for the different components of this hierarchical approach are illustrated in example simulations covering the random dopant-induced threshold voltage fluctuations, threshold voltage lowering, threshold voltage asymmetry, and drain current fluctuations.