PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

High-performance computing has recently seen a surge of interest in heterogeneous systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices offer tremendous potential for performance and efficiency in important large-scale applications of computational science. However, exploiting this potential can be challenging, as one must adapt to the specialized and rapidly evolving computing environment currently exhibited by GPUs. One way of addressing this challenge is to embrace better techniques and develop tools tailored to their needs. This article presents one simple technique, GPU run-time code generation (RTCG), along with PyCUDA and PyOpenCL, two open-source toolkits that support this technique. In introducing PyCUDA and PyOpenCL, this article proposes the combination of a dynamic, high-level scripting language with the massive performance of a GPU as a compelling two-tiered computing platform, potentially offering significant performance and productivity advantages over conventional single-tier, static systems. The concept of RTCG is simple and easily implemented using existing, robust infrastructure. Nonetheless it is powerful enough to support (and encourage) the creation of custom application-specific tools by its users. The premise of the paper is illustrated by a wide range of examples where the technique has been applied with considerable success.Comment: Submitted to Parallel Computing, Elsevie

Survey of Technologies for Web Application Development

Web-based application developers face a dizzying array of platforms, languages, frameworks and technical artifacts to choose from. We survey, classify, and compare technologies supporting Web application development. The classification is based on (1) foundational technologies; (2)integration with other information sources; and (3) dynamic content generation. We further survey and classify software engineering techniques and tools that have been adopted from traditional programming into Web programming. We conclude that, although the infrastructure problems of the Web have largely been solved, the cacophony of technologies for Web-based applications reflects the lack of a solid model tailored for this domain.Comment: 43 page

An Analysis of Scripting Languages for Research in Applied Computing

There are several scripting languages that exist today. However, some are used more frequently and popular than others. This is due to certain characteristics and features that they possess. Particularly in applied computing fields like software engineering, bioinformatics and computational biology, scripting languages are gaining popularity. This paper presents a comparative study of ten popular scripting languages that are used in the above mentioned fields/area. For making comparison, we have identified the factors against which these languages are evaluated. Accordingly, based on selected criteria we determine their suitability in the fields of software engineering, bioinformatics and computational biology research. This will serve as a guide to researchers to choose the appropriate scripting language in the various fields

Programming languages: a brief review

In this article we review the development of programming languages and classify them based on their structures and their applications

Implementation Model of Source Code Generator

The on demand generation of source code and its execution is essential if computers are expected to play an active role in information discovery and retrieval. This paper presents a model of implementation of a source code generator, whose purpose is to generate source code on demand. The implementation of the source code generator is fully configurable and its adoption to a new application is done by changing the generator configuration and not the generator itself. The advantage of using the source code generator is rapid and automatic development of a family of application once necessary program templates and generator configuration are made. The model of implementation of the source code generator is general and implemented source code generator can be used in different areas. We use a source code generator for dynamic generation of ontology supported Web services for data retrieval and for building of different kind of web application

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache