Software portability

About: Software portability is a research topic. Over the lifetime, 8987 publications have been published within this topic receiving 164922 citations. The topic is also known as: portability.

OpenARC: extensible OpenACC compiler framework for directive-based accelerator programming study

Abstract: Directive-based, accelerator programming models such as OpenACC have arisen as an alternative solution to program emerging Scalable Heterogeneous Computing (SHC) platforms. However, the increased complexity in the SHC systems incurs several challenges in terms of portability and productivity. This paper presents an open-sourced OpenACC compiler, called OpenARC, which serves as an extensible research framework to address those issues in the directive-based accelerator programming. This paper explains important design strategies and key compiler transformation techniques needed to implement the reference OpenACC compiler. Moreover, this paper demonstrates the efficacy of OpenARC as a research framework for directive-based programming study, by proposing and implementing OpenACC extensions in the OpenARC framework to 1) support hybrid programming of the unified memory and separate memory and 2) exploit architecture-specific features in an abstract manner. Porting thirteen standard OpenACC programs and three extended OpenACC programs to CUDA GPUs shows that OpenARC performs similarly to a commercial OpenACC compiler, while it serves as a high-level research framework.

Model-Driven Development and Operation of Multi-Cloud Applications: The MODAClouds Approach

Abstract: This books is open access under a CC BY 4.0 license. This book summarizes work being undertaken within the collaborative MODAClouds research project, which aims to facilitate interoperability between heterogeneous Cloud platforms and remove the constraints of deployment, portability, and reversibility for end users of Cloud services. Experts involved in the project provide a clear overview of the MODAClouds approach and explain how it operates in a variety of applications. While the wide spectrum of available Clouds constitutes a vibrant technical environment, many early-stage issues pose specific challenges from a software engineering perspective. MODAClouds will provide methods, a decision support system, and an open source IDE and run-time environment for the high-level design, early prototyping,semiautomatic code generation, and automatic deployment of applications on multiple Clouds. It will free developers from the need to commit to a fixed Cloud technology stack during software design and offer benefits in terms of cost savings, portability of applications and data between Clouds, reversibility (moving applications and data from Cloud to non-Cloud environments), risk management, quality assurance, and flexibility in the development process.

MA42 - A new frontal code for solving sparse unsymmetric systems

Abstract: We describe the design, implementation, and performance of a frontal code for the solution of large sparse unsymmetric systems of linear equations. The resulting software package, MA42, is included in Release 11 of the Harwell Subroutine Library and is intended to supersede the earlier MA32 package. We discuss in detail design changes from the earlier code, indicating the way in which they aid clarity, maintainability, and portability. The new design also permits extensive use of higher level BLAS kernels, which aid both modularity and efficiency. We illustrate the performance of our new code on practical problems on a CRAY Y-MP, an IBM 3090, and an IBM RISC System/6000. We indicate some directions for future development.

Flexible re-engineering of web sites

Abstract: Re-engineering transforms a final user interface into a logical representation that is manipulable enough to allow forward engineering to port a UI from one computing platform to another with maximum flexibility and minimal effort Re-engineering is used to adapt a UI to another context This adaptation is governed by two main tasks: the adaptation of the code itself to the new computing platform and the redesign of the UI to better suit the new constraints of the target platform (interaction capabilities, screen size,) To support this process, we have developed a reverse engineering tool that allows a flexible recovery of the presentation model from Web sites, adapting the reverse engineering to the target platforms, and a forward engineering tool that converts this model into any final executable UI, in particular expressed in VRML, WML,

Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model

Abstract: Generative pretrained transformer models have been popular recently due to their enhanced capabilities and performance. In contrast to many existing artificial intelligence models, generative pretrained transformer models can perform with very limited training data. Generative pretrained transformer 3 (GPT-3) is one of the latest releases in this pipeline, demonstrating human-like logical and intellectual responses to prompts. Some examples include writing essays, answering complex questions, matching pronouns to their nouns, and conducting sentiment analyses. However, questions remain with regard to its implementation in health care, specifically in terms of operationalization and its use in clinical practice and research. In this viewpoint paper, we briefly introduce GPT-3 and its capabilities and outline considerations for its implementation and operationalization in clinical practice through a use case. The implementation considerations include (1) processing needs and information systems infrastructure, (2) operating costs, (3) model biases, and (4) evaluation metrics. In addition, we outline the following three major operational factors that drive the adoption of GPT-3 in the US health care system: (1) ensuring Health Insurance Portability and Accountability Act compliance, (2) building trust with health care providers, and (3) establishing broader access to the GPT-3 tools. This viewpoint can inform health care practitioners, developers, clinicians, and decision makers toward understanding the use of the powerful artificial intelligence tools integrated into hospital systems and health care.