All music performances are generative to the extent that the actions of performers produce musical sounds, but in this article we focus on performative interaction with generative music in a more compositional sense. In particular we discuss how live coding of music involve the building and management of generative processes. We suggest that the human interaction with generative processes that occurs in live coding provides a unique perspective on the generative music landscape, especially significant is the way in which generative algorithms are represented in code to best afford interaction and modification during performance. We also discuss the features of generative processes that make them more or less suitable for live coding performances. We situate live coding practice within historical and theoretical contexts and ground the discussion with regular reference to our experiences performing in the live coding duo aa-cell.

Energy efficient embedded computing enables new application scenarios in mobile devices like software-defined radio and video processing. The hierarchical multiprocessor considered in this work may contain dozens or hundreds of resource efficient VLIW CPUs. Programming this number of CPU cores is a complex task requiring compiler support. The stream programming paradigm provides beneficial properties that help to support automatic partitioning. This work describes a compiler for streaming applications targeting the self-build hierarchical CoreVA-MPSoC multiprocessor platform. The compiler is supported by a programming model that is tailored to fit the streaming programming paradigm. We present a novel simulatedannealing (SA) based partitioning algorithm, called Smart SA. The overall speedup of Smart SA is 12.84 for an MPSoC with 16 CPU cores compared to a single CPU implementation. Comparison with a state of the art partitioning algorithm shows an average performance improvement of 34.07%. I . I N T R O D U C T I O NThe decreasing feature size of microelectronic circuits allows for the integration of more and more processing cores on a single chip. A Multiprocessor System-on-Chip (MPSoC) may consist of dozens of processing elements as CPU cores or specialized hardware accelerators connected by a highspeed communication infrastructure, i.e. a Network-On-Chip (NoC). However, mapping general purpose applications to a large number of MPSoC processing elements remains a nontrivial task. Manually writing low-level code for each core makes it difficult to experiment with different decompositions and mappings of computation to processors. Alternatively, higher-level programming frameworks allow the compiler to evaluate a larger design-space when mapping the application to different hardware configurations. Efficient mapping algorithms are important for finding optimized solutions. The Streaming paradigm provides regular and repeating computation and independent filters with explicit communication. This allows compilers to exploit the task more easily, data and pipeline parallelism commonly found in signal processing, multimedia, network processing, cryptology and similar application domains.A popular stream based programming language is StreamIt [1], [2]. The key principle of this language is to provide information about inherent parallelism of the program by using a structured data flow graph. This graph consisting of filters, pipelines, split-joins, and feedback loops.In this paper we present a compiler for the StreamIt Language targeting the self-build CoreVA-MPSoC architecture. The CoreVA-MPSoC is a highly scalable multiprocessor system based on a hierarchical communication infrastructure and the configurable VLIW 1 processor CoreVA.This paper is organized as follows: Section II describes our CoreVA-MPSoC hardware architecture. In Section III we discuss our StreamIt compiler with a focus on our novel simulated annealing partitioning algorithm (Smart SA). The communication model proposed in this work is presented in S...

Abstract-User interfaces for source code editing are a crucial component in any software development environment, and in many editors visual annotations (overlaid on the textual source code) are used to provide important contextual information to the programmer. This paper focuses on the real-time programming activity of 'cyberphysical' programming, and considers the type of visual annotations which may be helpful in this programming context.

The Cube" is a unique facility that combines 48 large multi-touch screens and very large-scale projection surfaces to form one of the world's largest interactive learning and engagement spaces. The Cube facility is part of the Queensland University of Technology's (QUT) newly established Science and Engineering Centre, designed to showcase QUT's teaching and research capabilities in the STEM (Science, Technology, Engineering, and Mathematics) disciplines. In this application paper we describe, the Cube, its technical capabilities, design rationale and practical day-to-day operations, supporting up to 70,000 visitors per week. Essential to the Cube's operation are five interactive applications designed and developed in tandem with the Cube's technical infrastructure. Each of the Cube's launch applications was designed and delivered by an independent team, while the overall vision of the Cube was shepherded by a small executive team. The diversity of design, implementation and integration approaches pursued by these five teams provides some insight into the challenges, and opportunities, presented when working with large distributed interaction technologies. We describe each of these applications in order to discuss the different challenges and user needs they address, which types of interactions they support and how they utilise the capabilities of the Cube facility.

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