Programming Languages and Compilers Commons^™

Introduction To Parallel Computation, Clinton Mckay

Graduate Student Theses, Dissertations, & Professional Papers

Introduction to Parallel Computing is a course designed to educate students on how to use the parallel libraries and tools provided by modern operating systems and massively parallel computer graphics hardware.

Using a series of lectures and hands-on exercises. Students will learn about parallel algorithms and concepts that will aid them in analyzing a problem and constructing a parallel solution, if possible, using the tools available to their disposal.

The course consists of lectures, projects, quizzes, and homework. The combination of these components will deliver the necessary domain knowledge to students, test them, and in the process train them to …

Integrated Development And Parallelization Of Automated Dicentric Chromosome Identification Software To Expedite Biodosimetry Analysis, Yanxin Li

Electronic Thesis and Dissertation Repository

Manual cytogenetic biodosimetry lacks the ability to handle mass casualty events. We present an automated dicentric chromosome identification (ADCI) software utilizing parallel computing technology. A parallelization strategy combining data and task parallelism, as well as optimization of I/O operations, has been designed, implemented, and incorporated in ADCI. Experiments on an eight-core desktop show that our algorithm can expedite the process of ADCI by at least four folds. Experiments on Symmetric Computing, SHARCNET, Blue Gene/Q multi-processor computers demonstrate the capability of parallelized ADCI to process thousands of samples for cytogenetic biodosimetry in a few hours. This increase in speed underscores the …

Cuda Web Api Remote Execution Of Cuda Kernels Using Web Services, Massimo J. Becker

Master's Theses

Massively parallel programming is an increasingly growing field with the recent introduction of general purpose GPU computing. Modern graphics processors from NVIDIA and AMD have massively parallel architectures that can be used for such applications as 3D rendering, financial analysis, physics simulations, and biomedical analysis. These massively parallel systems are exposed to programmers through in- terfaces such as NVIDIAs CUDA, OpenCL, and Microsofts C++ AMP. These frame- works expose functionality using primarily either C or C++. In order to use these massively parallel frameworks, programs being implemented must be run on machines equipped with massively parallel hardware. These requirements limit …