An OpenCL-based parallel acceleration of aSobel edge detection algorithm Using IntelFPGA technology

This paper examines the feasibility of using commercial out-of-the-box Reconfigurable Field Programmable Gate Array (FPGA) technology and the OpenCL framework to create efficient Sobel edge-detection implementation, which is considered a fundamental part in the field of image and video processing. The revised proposed approach was created at a high level of abstraction and executed on high commodity Intel FPGA platform. This was performed in a manner that was designed to allow the high-level compiler/synthesis tool to manipulate a task a parallelism model. The most promising FPGA and the naive implementations were compared to their single-core CPU software equivalents while manipulating local-memory, pipelining, loop unrolling, vectorization, internal channels mechanisms and memory coalescing to provide a much more effective hardware design. The run-time and the power consumption attributes were estimated for each implementation. The proposed FPGA based implementations were found to have significantly better runtime and power consumption with approximately up to 37 folds of improvement in the whole execution/transfer time, and up to 53 folds of improvement in energy consumption when compared to a specific single-core CPU based implementation.

The Nature of the Union of Mind and Body in Spinoza

The first chapter has three parts: – An analysis of the givens of the problem – A critique of the parallelism issue – The definition and nature of equality, which expresses the link between body and mind in Spinoza Spinoza conceives of the body and mind as one and the same thing expressed in two ways, under the attribute of thought, and under the attribute of extension. The problem is finding out how these two ways interrelate and come together, in order to understand human nature. Most commentators have interpreted the mind-body relationship according to the psychophysical parallelism model imported from Leibniz, which is unsatisfactory because it introduces a duality where there is unity, and reduces the differences of expression to the uniformity of self-replicating lines. That is why we must return to Spinoza's text, in order to inventory the terms he uses to expresses the mind-body union. The author's analysis reveals that the key concepts are equality and simultaneity. It then becomes necessary to examine psychophysical equality and simultaneity, and the special occasions on which they appear in Spinoza's corpus. That is why studying the affects becomes crucial – it makes it possible to comprehend the mind and body at the same time.

PAEAN: Portable and scalable runtime support for parallel Haskell dialects

Over time, several competing approaches to parallel Haskell programming have emerged. Different approaches support parallelism at various different scales, ranging from small multicores to massively parallel high-performance computing systems. They also provide varying degrees of control, ranging from completely implicit approaches to ones providing full programmer control. Most current designs assume a shared memory model at the programmer, implementation and hardware levels. This is, however, becoming increasingly divorced from the reality at the hardware level. It also imposes significant unwanted runtime overheads in the form of garbage collection synchronisation etc. What is needed is an easy way to abstract over the implementation and hardware levels, while presenting a simple parallelism model to the programmer. The PArallEl shAred Nothing runtime system design aims to provide a portable and high-level shared-nothing implementation platform for parallel Haskell dialects. It abstracts over major issues such as work distribution and data serialisation, consolidating existing, successful designs into a single framework. It also provides an optional virtual shared-memory programming abstraction for (possibly) shared-nothing parallel machines, such as modern multicore/manycore architectures or cluster/cloud computing systems. It builds on, unifies and extends, existing well-developed support for shared-memory parallelism that is provided by the widely used GHC Haskell compiler. This paper summarises the state-of-the-art in shared-nothing parallel Haskell implementations, introduces the PArallEl shAred Nothing abstractions, shows how they can be used to implement three distinct parallel Haskell dialects, and demonstrates that good scalability can be obtained on recent parallel machines.

PARALLEL ALGORITHMS FOR MAPPING SHORT DEGENERATE AND WEIGHTED DNA SEQUENCES TO A REFERENCE GENOME

One of the most ambitious trends in current biomedical research is the large-scale genomic sequencing of patients. Novel high-throughput (or next-generation) sequencing technologies have redefined the way genome sequencing is performed. They are able to produce millions of short sequences (reads) in a single experiment, and with a much lower cost than previously possible. Due to this massive amount of data, efficient algorithms for mapping these sequences to a reference genome are in great demand, and recently, there has been ample work for publishing such algorithms. One important feature of these algorithms is the support of multithreaded parallel computing in order to speedup the mapping process. In this paper, we design parallel algorithms, which make use of the message-passing parallelism model, to address this problem efficiently. The proposed algorithms also take into consideration the probability scores assigned to each base for occurring in a specific position of a sequence. In particular, we present parallel algorithms for mapping short degenerate and weighted DNA sequences to a reference genome.

Overview of the Force Scientific Parallel Language

The Force parallel programming language designed for large-scale shared-memory multiprocessors is presented. The language provides a number of parallel constructs as extensions to the ordinary Fortran language and is implemented as a two-level macro preprocessor to support portability across shared memory multiprocessors. The global parallelism model on which the Force is based provides a powerful parallel language. The parallel constructs, generic synchronization, and freedom from process management supported by the Force has resulted in structured parallel programs that are ported to the many multiprocessors on which the Force is implemented. Two new parallel constructs for looping and functional decomposition are discussed. Several programming examples to illustrate some parallel programming approaches using the Force are also presented.