Thesis (MMus (Music))--University of Stellenbosch, 2009. / The initiation and establishment of community music projects have been increasing in number in South Africa in the last decade due to the growing interest in these projects’ beneficial outcomes. Music education, music activities and a myriad of opportunities through music are provided to under-privileged communities who would otherwise be deprived thereof. The Redefine Music Education Project is a community music project situated in Kuils River and which draws learners from local impoverished communities and townships. The efficient management of project, staff and learner commitment, and community involvement has resulted in various project and learner achievements. However, it has also undergone several setbacks and faces frequent challenges. Due to the Redefine Music Education Project’s success rate and sustained years of operation, it is considered as one of the Western Cape’s reputable community music projects. This research study sets out by evaluating the need and role of a community music project in disadvantaged communities as well as describing the qualities that make a community music project successful. The research uncovered the impact that such a project has on the individual and on local communities in the Western Cape. A noteworthy result of the study is the fact that it serves as guidance and motivation to other operating and upcoming community music projects. It also provides and opens further opportunities of study and research regarding music in the community. / Die inisiëring en vestiging van gemeenskaps-musiekprojekte het in die laaste dekade in Suid-Afrika toegeneem vanweë die groeiende belangstelling in die voordelige uitkomste van hierdie projekte. Hierdie projekte bied musiekopvoeding, musiekaktiwiteite en ontsluit geleenthede deur musiek aan minder bevoorregde gemeenskappe wat andersins nie daarmee in aanraking sou kom nie. Die Redefine Music Education Project is 'n gemeenskaps-musiekprojek geleë in Kuilsrivier. Die projek staan grootliks in diens van leerders uit plaaslike verarmde gemeenskappe en townships. Die doeltreffende bestuur van die projek, personeel en leerder-toewyding, en gemeenskapsbetrokkenheid het verskeie projek- en leerderprestasies tot gevolg gehad. Die projek het egter ook verskeie terugslae ervaar en staar voortdurende uitdagings in die gesig. As gevolg van die Redefine Music Education Project se suksesse en die hoeveelheid jare wat dit reeds bestaan, word dit gereken as een van die Wes-Kaap se maatgewende gemeenskaps-musiekprojekte. Hierdie navorsing evalueer die behoefte aan en rol van 'n gemeenskaps-musiekprojek in minder bevoorregde gemeenskape. Dit ondersoek ook die kwaliteite wat so 'n projek help om suksesvol te wees. Die navorsing toon uiteindelik ook die impak wat so 'n projek op individue en op plaaslike gemeenskappe in die Wes-Kaap het. 'n Betekenisvolle resultaat van die studie is dat dit as gids en motivering dien vir ander huidige en toekomstige gemeenskaps-musiekprojekte. Dit beskryf ook verdere geleenthede vir studie en navorsing ten opsigte van musiek in die gemeenskap.

Application domains such as Bio-informatics, DSP, Structural Biology, Fluid Dynamics, high resolution direction finding, state estimation, adaptive noise cancellation etc. demand high performance computing solutions for their simulation environments. The core computations of these applications are in Numerical Linear Algebra (NLA) kernels. Direct solvers are predominantly required in the domains like DSP, estimation algorithms like Kalman Filter etc, where the matrices on which operations need to be performed are either small or medium sized, but dense. Faddeev's Algorithm is often used for solving dense linear system of equations. Modified Faddeev's algorithm (MFA) is a general algorithm on which LU decomposition, QR factorization or SVD of matrices can be realized. MFA has the good property of realizing a host of matrix operations by computing the Schur complements on four blocked matrices, thereby reducing the overall computation requirements. We will use MFA as a representative Direct Solver in this work. We further discuss Given's rotation based QR algorithm for Decomposition of any matrix, often used to solve the linear least square problem. Systolic Array Architectures are widely accepted ASIC solutions for NLA algorithms. But the \can of worms" associated with this traditional solution spawns the need for alternative solutions. While popular custom hardware solution in form of systolic arrays can deliver high performance, but because of their rigid structure they are not scalable and reconfigurable, and hence not commercially viable. We show how a Reconfigurable computing platform can serve to contain the \can of worms". REDEFINE, a coarse grained runtime reconfigurable architecture has been used for systolic actualization of NLA kernels. We elaborate upon streaming NLA-specific enhancements to REDEFINE in order to meet expected performance goals. We explore the need for an algorithm aware custom compilation framework. We bring about a proposition to realize Faddeev's Algorithm on REDEFINE. We show that REDEFINE performs several times faster than traditional GPPs. Further we direct our interest to QR Decomposition to be the next NLA kernel as it ensures better stability than LU and other decompositions. We use QR Decomposition as a case study to explore the design space of the proposed solution on REDEFINE. We also investigate the architectural details of the Custom Functional Units (CFU) for these NLA kernels. We determine the right size of the sub-array in accordance with the optimal pipeline depth of the core execution units and the number of such units to be used per sub-array. The framework used to realize QR Decomposition can be generalized for the realization of other algorithms dealing with decompositions like LU, Faddeev's Algorithm, Gauss-Jordon etc with different CFU definitions .

Qualitative research was conducted in order to explore the generation of social and musical capital through music therapy sessions and musical activities with youths attending the Redefine Community Music Project in the Western Cape. This study was conducted from the perspective of Wood‟s Matrix Model (2006) of music therapy where different interlinking musical activities in a range of contexts are shown to extend the benefits of individual music therapy. Data were gathered through conducting a case study with one of the ensemble groups in the Redefine Community Music Project. This group attended music therapy sessions, and the members of the group took part in ensemble rehearsals in preparation for the bi-annual public performance. Data were analysed through using Ansdell and Pavlicevic‟s (2001) method of qualitative content analysis, as well as the analytic technique of open coding proposed by Gibbs (2007). The findings suggest that the multi-faceted format of the Matrix Model of music therapy (Wood, 2006), as reflected in the socio-musical networks of the Redefine Community Music Project, offered participants enhanced opportunities to generate social and musical capital. By facilitating diverse opportunities for musicing in various contexts, participants were enabled to accrue a broad range of social and musical capital with which to create valuable relationships to the self and with others. It is suggested that music therapists and community musicians wishing to facilitate the generation of social capital through music flexibly adapt their practices to the socio-musical needs of the communities in which they work and offer diverse formats of musicing in which social and musical capital may be generated. In this manner individuals and communities may be empowered to cultivate relationships of diverse value in a creative way. / Dissertation (MMus)--University of Pretoria, 2012. / Music / unrestricted

REDEFINE is a reconfigurable SoC architecture that provides a unique platform for high performance and low power computing by exploiting the synergistic interaction between coarse grain dynamic dataflow model of computation (to expose abundant parallelism in the applications) and runtime composition of efficient compute structures (on the reconfigurable computation resources). Computer architectures based on the dynamic dataflow model of computation have to be an infinite resource implementation to be able to exploit all available parallelism in all applications. It is not feasible for any real architectural implementation. When limited resource implementations are considered, there is a possibility of loss of performance (inability to efficiently exploit available parallelism). In this thesis, we study the throttling of execution in the REDEFINE architecture to maximize the architecture efficiency. We have formulated it as a design space exploration problem at two levels i.e. architectural configurations and throttling schemes. Reduced feature/high level simulation or feature specific analytical approaches are very useful for the selective study/exploration of early in design phase architectures/systems. Our approach is similar to that of SEASAME Framework which is used for the study of MPSoC (Multiprocessor SoC) architectures. We have used abstraction (feature reduction) at the levels of architecture and model of computation to make the problem approachable and practically feasible. A feature specific fast hybrid (mixed level) simulation framework for the early in design phase study is developed and implemented for the huge design space exploration (1284 throttling schemes, 128 architectural configurations and 10 applications i.e. 1.6 million executions). We have done performance modeling in terms of selection of important performance criteria, ranking of the explored throttling schemes and investigation of the effectiveness of the design space exploration using statistical hypothesis testing. We found some interesting obvious/intuitive and some non-obvious/counterintuitive results. The two performance criteria namely Exec.T and Avg.TU were found sufficient to represent the performance and the resource usage characteristics of the architecture independent of the throttling schemes, the architectural configurations and the applications. The ranking of the throttling schemes based on the selected performance criteria is found to be statistically very significant. The intuitive throttling schemes span the range of performance from the best to the worst. We found absence of trade-off amongst all of the performance criteria. The best throttling schemes give appreciable overall performance (25%) and resource usage (37%) gains in the throttling unit simultaneously. The design space exploration of the throttling schemes is found to be fine and uniform.