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.

Portability and interoperability between clouds: challenges and case study

Abstract: The greatest challenge beyond trust and security for the long-term adoption of cloud computing is the interoperability between clouds. In the context of world-wide tremendous activities against the vendor lock-in and lack of integration of cloud computing services, keeping track of the new concepts and approaches is also a challenge. We considered useful to provide in this paper a snapshot of these concepts and approaches followed by a proposal of their classification. A new approach in providing cloud portability is also revealed.

Hardware abstraction layer (hal) for a robot

Abstract: Methods and apparatus that provide a hardware abstraction layer (HAL) for a robot are disclosed. A HAL can reside as a software layer or as a firmware layer residing between robot control software and underlying robot hardware and/or an operating system for the hardware. The HAL provides a relatively uniform abstract for aggregates of underlying hardware such that the underlying robotic hardware is transparent to perception and control software, i.e., robot control software. This advantageously permits robot control software to be written in a robot-independent manner. Developers of robot control software are then freed from tedious lower level tasks. Portability is another advantage. For example, the HAL efficiently permits robot control software developed for one robot to be ported to another. In one example, the HAL permits the same navigation algorithm to be ported from a wheeled robot and used on a humanoid legged robot.

Titanium Language Reference Manual

Abstract: Titanium is a dialect of Java for large-scale scientific computing. The primary goal is a language that has high performance on large scale multiprocessors, including massively parallel processors and workstation clusters with one or more processors per node. Secondary goals include safety, portability, and support for building complex data structures. The main additions to Java are immutable classes, multi-dimensional arrays, an explicitly parallel SPMD model, and zone-based memory management. This document informally describes our current design for the Titanium language. It is in the form of a set of changes to Java, version 1.0.

System and method for facilitating access to network based services

Abstract: A system and method for facilitating web service component access. A One Logical View to Broker (OLVB) Application Program Interface (API) is established for application (402) in order to reduce the complexity of the application interface and subsequently increase the portability of application (402). Network Service Broker related parameters (204,304) allows the solicitation of the best match Network Service Broker or web service component, while hiding the selection detail from application (402). Real-time business relationships between Service Provisioning Infrastructure (208) and Network Service Brokers (212,232,238) is facilitated by using matchmaking function (416) within lookup function (414).

Partitioning streaming parallelism for multi-cores: a machine learning based approach

Abstract: Stream based languages are a popular approach to expressing parallelism in modern applications. The efficient mapping of streaming parallelism to multi-core processors is, however, highly dependent on the program and underlying architecture. We address this by developing a portable and automatic compiler-based approach to partitioning streaming programs using machine learning. Our technique predicts the ideal partition structure for a given streaming application using prior knowledge learned off-line. Using the predictor we rapidly search the program space (without executing any code) to generate and select a good partition. We applied this technique to standard StreamIt applications and compared against existing approaches. On a 4-core platform, our approach achieves 60% of the best performance found by iteratively compiling and executing over 3000 different partitions per program. We obtain, on average, a 1.90x speedup over the already tuned partitioning scheme of the StreamIt compiler. When compared against a state-of-the-art analytical, model-based approach, we achieve, on average, a 1.77x performance improvement. By porting our approach to a 8-core platform, we are able to obtain 1.8x improvement over the StreamIt default scheme, demonstrating the portability of our approach.