high performance computing on graphics processing units: hgpu.org

Ray tracing is a very popular way to draw 3-D scenes onto a 2-D image. The technique produces a very high degree of visual realism with regard to shadows, reflection, and refraction. The drawback of this technique is the fact that it is extremely computationally expensive. This expense has been a barrier to using ray […]

I describe an approach to compiling common idioms in R code directly to native machine code and illustrate it with several examples. Not only can this yield significant performance gains, but it allows us to use new approaches to computing in R. Importantly, the compilation requires no changes to R itself, but is done entirely […]

The general purpose computing on graphics processing unit (GP-GPU) has emerged as a new cost effective parallel computing paradigm in high performance computing research that enables large amount of data to be processed in parallel. Large scale scientific data intensive applications have been playing an important role in modern high performance computing research. A common […]

Physically based cloth simulation in computer graphics has come a long way since the 1980s. Although extensive methods have been developed, physically based cloth animation remains challenging in a number of aspects, including the efficient simulation of complex internal dynamics, better performance and the generation of more effects of friction in collisions, to name but […]

Directive-based programming models provide high-level of abstraction thus hiding complex low-level details of the underlying hardware from the programmer. One such model is OpenACC that is also a portable programming model allowing programmers to write applications that offload portions of work from a host CPU to an attached accelerator (GPU or a similar device). The […]

The past years have witnessed many dedicated open-source projects that built and maintain implementations of Support Vector Machines (SVM), parallelized for GPU, multi-core CPUs and distributed systems. Up to this point, no comparable effort has been made to parallelize the Elastic Net, despite its popularity in many high impact applications, including genetics, neuroscience and systems […]

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical […]

Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA — a parallel computing platform and programming model designed to ease the development of GPU programming — fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, […]

Real-time and archrival data documents are increases as fast as or faster than computing power now a days. Document classification using k-nn classification algorithm takes more time in searching nearer neighbors in large training dataset, it include large number of computations. The time for classification increases in proportion to the number of documents. Therefore it […]

A multi-dimensional data model provides a good conceptual view of the data in data warehousing and On-Line Analytical Processing (OLAP). A typical representation of such a data model is as a multi-dimensional array which is well suited when the array is dense. If the array is sparse, i.e., has a few number of non-zero elements […]

As parallel and heterogeneous computing becomes more and more a necessity for implementing high performance simulators, it becomes increasingly harder for scientists and engineers without experience in high performance computing to achieve good performance. Even for those who knows how to write efficient code the process for doing so is time consuming and error prone, […]

In the course of less than a decade, Graphics Processing Units (GPUs) have evolved from narrowly scoped application specific accelerators to general-purpose parallel machines capable of accommodating an ever-growing set of algorithms. At the same time, programming GPUs appears to have become trapped around an attractor characterised by ad-hoc practices, non-portable implementations and inexact, uninformative […]